├── .env.example ├── .github ├── logo.png └── social-preview.png ├── .gitignore ├── Dockerfile ├── LICENSE ├── README.md ├── assets ├── apple-touch-icon.png ├── deepseek-dark-mode.png ├── favicon-16x16.png ├── favicon-32x32.png └── favicon.ico ├── index.ts ├── package-lock.json ├── package.json ├── smithery.yaml ├── src ├── docs │ ├── deepseek-api-example.md │ └── llms-full.txt ├── index.ts └── types.ts ├── tsconfig.json └── util.ts /.env.example: -------------------------------------------------------------------------------- 1 | # DeepSeek API Configuration 2 | DEEPSEEK_API_KEY=your-api-key-here 3 | -------------------------------------------------------------------------------- /.github/logo.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/DMontgomery40/deepseek-mcp-server/1cf59710f952985251b4ce3d49b25e6ec6718f4c/.github/logo.png -------------------------------------------------------------------------------- /.github/social-preview.png: -------------------------------------------------------------------------------- 1 | 2 | 3 | 1. Go to GitHub repository settings 4 | 2. Click on "Social preview" under the repository name 5 | 3. Click "Edit" 6 | 4. Upload the assets/favicon-32x32.png file 7 | 5. GitHub will help resize and position it appropriately 8 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | node_modules/ 2 | build/ 3 | .env 4 | *.log 5 | .DS_Store 6 | -------------------------------------------------------------------------------- /Dockerfile: -------------------------------------------------------------------------------- 1 | # Generated by https://smithery.ai. See: https://smithery.ai/docs/config#dockerfile 2 | FROM node:18-alpine AS builder 3 | 4 | WORKDIR /app 5 | 6 | # Copy the necessary files 7 | COPY package.json package-lock.json ./ 8 | COPY tsconfig.json ./ 9 | COPY src ./src 10 | 11 | # Install dependencies and build the project 12 | RUN npm install && npm run build 13 | 14 | # Use a smaller base image for the release 15 | FROM node:18-alpine AS release 16 | 17 | WORKDIR /app 18 | 19 | # Copy only the built output and necessary files 20 | COPY --from=builder /app/build ./build 21 | COPY --from=builder /app/package.json ./package.json 22 | COPY --from=builder /app/package-lock.json ./package-lock.json 23 | 24 | # Install production dependencies only 25 | RUN npm install --production 26 | 27 | # Set environment variable 28 | ENV NODE_ENV=production 29 | 30 | # Entry point 31 | ENTRYPOINT ["node", "build/index.js"] -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2025 David Montgomery 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # DeepSeek MCP Server 2 | 3 | A Model Context Protocol (MCP) server for the DeepSeek API, allowing seamless integration of DeepSeek's powerful language models with MCP-compatible applications like Claude Desktop. 4 | 5 | ## *Anonymously* use DeepSeek API -- Only a proxy is seen on the other side 6 | 7 | DeepSeek Server MCP server 8 | 9 | 10 | [![npm version](https://img.shields.io/npm/v/deepseek-mcp-server)](https://www.npmjs.com/package/deepseek-mcp-server) 11 | [![npm downloads](https://img.shields.io/npm/dm/deepseek-mcp-server)](https://www.npmjs.com/package/deepseek-mcp-server) 12 | [![GitHub issues](https://img.shields.io/github/issues/DMontgomery40/deepseek-mcp-server)](https://github.com/DMontgomery40/deepseek-mcp-server/issues) 13 | [![GitHub forks](https://img.shields.io/github/forks/DMontgomery40/deepseek-mcp-server)](https://github.com/DMontgomery40/deepseek-mcp-server/network) 14 | [![GitHub stars](https://img.shields.io/github/stars/DMontgomery40/deepseek-mcp-server)](https://github.com/DMontgomery40/deepseek-mcp-server/stargazers) 15 | [![GitHub license](https://img.shields.io/github/license/DMontgomery40/deepseek-mcp-server?color=blue)](https://github.com/DMontgomery40/deepseek-mcp-server/blob/main/LICENSE) 16 | 17 | ## Installation 18 | 19 | ### Installing via Smithery 20 | 21 | To install DeepSeek MCP Server for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@dmontgomery40/deepseek-mcp-server): 22 | 23 | ```bash 24 | npx -y @smithery/cli install @dmontgomery40/deepseek-mcp-server --client claude 25 | ``` 26 | 27 | ### Manual Installation 28 | ```bash 29 | npm install -g deepseek-mcp-server 30 | ``` 31 | ### Usage with Claude Desktop 32 | 33 | Add this to your `claude_desktop_config.json`: 34 | 35 | ```json 36 | { 37 | "mcpServers": { 38 | "deepseek": { 39 | "command": "npx", 40 | "args": [ 41 | "-y", 42 | "deepseek-mcp-server" 43 | ], 44 | "env": { 45 | "DEEPSEEK_API_KEY": "your-api-key" 46 | } 47 | } 48 | } 49 | } 50 | ``` 51 | 52 | ## Features 53 | 54 | > Note: The server intelligently handles these natural language requests by mapping them to appropriate configuration changes. You can also query the current settings and available models: 55 | 56 | - User: "What models are available?" 57 | - Response: Shows list of available models and their capabilities via the models resource. 58 | - User: "What configuration options do I have?" 59 | - Response: Lists all available configuration options via the model-config resource. 60 | - User: "What is the current temperature setting?" 61 | - Response: Displays the current temperature setting. 62 | - User: "Start a multi-turn conversation. With the following settings: model: 'deepseek-chat', make it not too creative, and 63 | allow 8000 tokens." 64 | - Response: *Starts a multi-turn conversation with the specified settings.* 65 | 66 | ### Automatic Model Fallback if R1 is down 67 | 68 | - If the primary model (R1) is down (called `deepseek-reasoner` in the server), the server will automatically attempt to try with v3 (called `deepseek-chat` in the server) 69 | > Note: You can switch back and forth anytime as well, by just giving your prompt and saying "use `deepseek-reasoner`" or "use `deepseek-chat`" 70 | - V3 is recommended for general purpose use, while R1 is recommended for more technical and complex queries, primarily due to speed and token usage 71 | 72 | ### Resource discovery for available models and configurations: 73 | * Custom model selection 74 | * Temperature control (0.0 - 2.0) 75 | * Max tokens limit 76 | * Top P sampling (0.0 - 1.0) 77 | * Presence penalty (-2.0 - 2.0) 78 | * Frequency penalty (-2.0 - 2.0) 79 | 80 | ## Enhanced Conversation Features 81 | 82 | **Multi-turn conversation support:** 83 | * Maintains complete message history and context across exchanges 84 | * Preserves configuration settings throughout the conversation 85 | * Handles complex dialogue flows and follow-up chains automatically 86 | 87 | This feature is particularly valuable for two key use cases: 88 | 89 | 1. **Training & Fine-tuning:** 90 | Since DeepSeek is open source, many users are training their own versions. The multi-turn support provides properly formatted conversation data that's essential for training high-quality dialogue models. 91 | 92 | 2. **Complex Interactions:** 93 | For production use, this helps manage longer conversations where context is crucial: 94 | * Multi-step reasoning problems 95 | * Interactive troubleshooting sessions 96 | * Detailed technical discussions 97 | * Any scenario where context from earlier messages impacts later responses 98 | 99 | The implementation handles all context management and message formatting behind the scenes, letting you focus on the actual interaction rather than the technical details of maintaining conversation state. 100 | 101 | ## Fill-in-the-Middle (FIM) Completion Tool 102 | 103 | The DeepSeek MCP Server now supports the FIM (Fill-in-the-Middle) completion endpoint, which is especially useful for code completion, refactoring, and filling in missing code blocks. 104 | 105 | **Limitations:** 106 | - The FIM endpoint has a 4,096 token (4k) context window. If your prefix + suffix + completion exceeds this, the request will be truncated or may fail. 107 | - FIM is best suited for code and structured text, not general conversation. 108 | 109 | ### How to Use 110 | 111 | You can invoke the FIM tool via MCP clients that support tools, or programmatically. The tool is named `fim_completion` and accepts the following parameters: 112 | 113 | - `prefix` (string, required): The text before the missing section. 114 | - `suffix` (string, required): The text after the missing section. 115 | - `model` (string, optional, default: `deepseek-fim`): The FIM model to use. 116 | - `temperature` (number, optional, default: 0.7): Sampling temperature. 117 | - `max_tokens` (number, optional, default: 1024): Maximum tokens to generate for the middle section. 118 | - `top_p` (number, optional, default: 1.0): Top-p sampling parameter. 119 | - `frequency_penalty` (number, optional, default: 0.1): Frequency penalty. 120 | - `presence_penalty` (number, optional, default: 0): Presence penalty. 121 | - `stream` (boolean, optional, default: false): Whether to stream the response. 122 | 123 | #### Example Usage 124 | 125 | ```json 126 | { 127 | "tool": "fim_completion", 128 | "params": { 129 | "prefix": "def add(a, b):\n return a + b\n\ndef multiply(a, b):\n ", 130 | "suffix": "\n return result\n", 131 | "temperature": 0.2, 132 | "max_tokens": 64 133 | } 134 | } 135 | ``` 136 | 137 | The response will contain the generated code or text that fits between the prefix and suffix. 138 | 139 | **When to use FIM:** 140 | - Completing code blocks where the middle is missing 141 | - Refactoring code by providing the start and end, and letting the model fill in the logic 142 | - Generating boilerplate or repetitive code patterns 143 | - Any scenario where you want the model to generate content that fits between two known sections 144 | 145 | ## Testing with MCP Inspector 146 | 147 | You can test the server locally using the MCP Inspector tool: 148 | 149 | 1. Build the server: 150 | ```bash 151 | npm run build 152 | ``` 153 | 154 | 2. Run the server with MCP Inspector: 155 | ```bash 156 | # Make sure to specify the full path to the built server 157 | npx @modelcontextprotocol/inspector node ./build/index.js 158 | ``` 159 | 160 | The inspector will open in your browser and connect to the server via stdio transport. You can: 161 | - View available tools 162 | - Test chat completions with different parameters 163 | - Debug server responses 164 | - Monitor server performance 165 | 166 | Note: The server uses DeepSeek's R1 model (deepseek-reasoner) by default, which provides state-of-the-art performance for reasoning and general tasks. 167 | 168 | ## License 169 | 170 | MIT 171 | -------------------------------------------------------------------------------- /assets/apple-touch-icon.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/DMontgomery40/deepseek-mcp-server/1cf59710f952985251b4ce3d49b25e6ec6718f4c/assets/apple-touch-icon.png -------------------------------------------------------------------------------- /assets/deepseek-dark-mode.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/DMontgomery40/deepseek-mcp-server/1cf59710f952985251b4ce3d49b25e6ec6718f4c/assets/deepseek-dark-mode.png -------------------------------------------------------------------------------- /assets/favicon-16x16.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/DMontgomery40/deepseek-mcp-server/1cf59710f952985251b4ce3d49b25e6ec6718f4c/assets/favicon-16x16.png -------------------------------------------------------------------------------- /assets/favicon-32x32.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/DMontgomery40/deepseek-mcp-server/1cf59710f952985251b4ce3d49b25e6ec6718f4c/assets/favicon-32x32.png -------------------------------------------------------------------------------- /assets/favicon.ico: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/DMontgomery40/deepseek-mcp-server/1cf59710f952985251b4ce3d49b25e6ec6718f4c/assets/favicon.ico -------------------------------------------------------------------------------- /index.ts: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env node 2 | import { McpServer, ResourceTemplate } from '@modelcontextprotocol/sdk/server/mcp.js'; 3 | import { ServerCapabilities, ErrorCode, McpError, ListPromptsRequestSchema, GetPromptRequestSchema } from '@modelcontextprotocol/sdk/types.js'; 4 | import { StdioServerTransport } from '@modelcontextprotocol/sdk/server/stdio.js'; 5 | import { array, boolean, optional, string, z, literal } from 'zod'; 6 | import axios, { AxiosError } from 'axios'; 7 | import * as dotenv from 'dotenv'; 8 | import { ConfigSchema, ModelConfig, interpretConfigInstruction } from './util.js'; 9 | import type { DeepSeekResponse, ModelsResponse } from './types.js'; 10 | 11 | // Load environment variables 12 | dotenv.config(); 13 | const DEEPSEEK_API_KEY = process.env.DEEPSEEK_API_KEY; 14 | if (!DEEPSEEK_API_KEY) throw new McpError(ErrorCode.InvalidRequest, 'Missing DEEPSEEK_API_KEY'); 15 | 16 | // Configure server capabilities 17 | const capabilities: ServerCapabilities = { 18 | resources: { enabled: true }, 19 | tools: { enabled: true }, 20 | prompts: { 21 | enabled: true, 22 | templates: ['system', 'chat'], 23 | defaultTemplate: 'chat' 24 | } 25 | }; 26 | 27 | 28 | const transport = new StdioServerTransport(); 29 | await server.connect(transport); 30 | console.log('Connected to server'); 31 | 32 | // Define available prompts 33 | const PROMPTS = { 34 | "system": { 35 | name: "system", 36 | description: "Set system behavior for the AI", 37 | arguments: [ 38 | { 39 | name: "content", 40 | description: "System instruction", 41 | required: true 42 | }, 43 | { 44 | name: "temperature", 45 | description: "Response temperature (0-1)", 46 | required: false 47 | } 48 | ] 49 | }, 50 | "chat": { 51 | name: "chat", 52 | description: "Chat with the AI", 53 | arguments: [ 54 | { 55 | name: "content", 56 | description: "User message", 57 | required: true 58 | }, 59 | { 60 | name: "history", 61 | description: "Previous conversation messages", 62 | required: false 63 | }, 64 | { 65 | name: "temperature", 66 | description: "Response temperature (0-1)", 67 | required: false 68 | }, 69 | { 70 | name: "shouldSummarize", 71 | description: "Whether to summarize the conversation", 72 | required: false 73 | } 74 | ] 75 | } 76 | }; 77 | 78 | // Create Server 79 | const server = new McpServer({ 80 | name: 'deepseek-mcp-server', 81 | version: '1.1.0', 82 | capabilities 83 | }); 84 | 85 | // List available prompts handler 86 | server.setRequestHandler(ListPromptsRequestSchema, async () => { 87 | return { 88 | prompts: Object.values(PROMPTS) 89 | }; 90 | }); 91 | 92 | // Get specific prompt handler 93 | server.setRequestHandler(GetPromptRequestSchema, async (request) => { 94 | const prompt = PROMPTS[request.params.name]; 95 | if (!prompt) { 96 | throw new McpError(ErrorCode.InvalidRequest, `Prompt not found: ${request.params.name}`); 97 | } 98 | 99 | const args = request.params.arguments || {}; 100 | 101 | if (request.params.name === "system") { 102 | if (!args.content) { 103 | throw new McpError(ErrorCode.InvalidRequest, "System prompt requires content argument"); 104 | } 105 | 106 | return { 107 | messages: [ 108 | { 109 | role: 'system', 110 | content: { 111 | type: 'text', 112 | text: args.content 113 | } 114 | } 115 | ], 116 | temperature: args.temperature 117 | }; 118 | } 119 | 120 | if (request.params.name === "chat") { 121 | if (!args.content) { 122 | throw new McpError(ErrorCode.InvalidRequest, "Chat prompt requires content argument"); 123 | } 124 | 125 | const messages = [ 126 | ...(args.history || []), 127 | { 128 | role: 'user', 129 | content: { 130 | type: 'text', 131 | text: args.content 132 | } 133 | } 134 | ]; 135 | 136 | if (args.shouldSummarize) { 137 | messages.push({ 138 | role: 'user', 139 | content: { 140 | type: 'text', 141 | text: 'Please summarize our conversation into key points needed for continuing the discussion.' 142 | } 143 | }); 144 | } 145 | 146 | return { 147 | messages, 148 | temperature: args.temperature ?? modelConfig.temperature 149 | }; 150 | } 151 | 152 | throw new McpError(ErrorCode.InternalError, "Prompt implementation not found"); 153 | }); 154 | 155 | 156 | const client = new McpClient({ 157 | awwa: { 158 | command: 'npx', 159 | args: ['-y', '@modelcontextprotocol/client-awwa', 'http://localhost:3000'] 160 | } 161 | }); 162 | 163 | 164 | // State Management 165 | let modelConfig: ModelConfig = ConfigSchema.parse({}); 166 | 167 | // Define Message Schema 168 | const MessageSchema = z.object({ 169 | role: z.enum(['system', 'user', 'assistant']), 170 | content: z.object({ 171 | type: z.literal('text'), 172 | text: z.string() 173 | }) 174 | }); 175 | 176 | // 1. Register RESOURCES first (they provide data) 177 | server.resource( 178 | 'model-configuration', 179 | new ResourceTemplate('model-config://main', { 180 | list: undefined 181 | }), 182 | async (uri: URL) => ({ 183 | contents: [{ 184 | uri: uri.href, 185 | text: JSON.stringify({ 186 | type: 'model-config', 187 | data: modelConfig 188 | }) 189 | }] 190 | }) 191 | ); 192 | 193 | server.resource( 194 | 'models', 195 | 'models://list', 196 | async (uri: URL) => { 197 | try { 198 | const response = await axios.get( 199 | 'https://api.deepseek.com/models', 200 | { 201 | headers: { 202 | 'Authorization': `Bearer ${DEEPSEEK_API_KEY}`, 203 | 'Content-Type': 'application/json' 204 | } 205 | } 206 | ); 207 | 208 | return { 209 | contents: [{ 210 | uri: uri.href, 211 | text: JSON.stringify(response.data, null, 2) 212 | }] 213 | }; 214 | } catch (error) { 215 | const axiosError = error as AxiosError; 216 | if (axiosError.response) { 217 | throw new McpError( 218 | ErrorCode.InvalidRequest, 219 | `API error: ${JSON.stringify(axiosError.response.data)}` 220 | ); 221 | } 222 | throw new McpError(ErrorCode.InternalError, 'Failed to fetch models list'); 223 | } 224 | } 225 | ); 226 | 227 | // 2. Register TOOLS second (they perform actions) 228 | server.tool( 229 | 'chat-completion', 230 | { 231 | messages: z.array(MessageSchema), 232 | temperature: z.number().optional(), 233 | max_tokens: z.number().optional(), 234 | stop: z.array(z.string()).optional() 235 | }, 236 | async ({ messages, temperature, max_tokens, stop }) => { 237 | try { 238 | const isReasoner = modelConfig.model?.includes('reasoner'); 239 | const payload: Record = { 240 | messages, 241 | model: modelConfig.model || 'deepseek-reasoner', 242 | max_tokens: max_tokens ?? modelConfig.max_tokens, 243 | stop 244 | }; 245 | 246 | if (!isReasoner) { 247 | payload.temperature = temperature ?? modelConfig.temperature; 248 | } 249 | 250 | const response = await axios.post( 251 | 'https://api.deepseek.com/v1/chat/completions', 252 | payload, 253 | { 254 | headers: { 255 | 'Authorization': `Bearer ${DEEPSEEK_API_KEY}`, 256 | 'Content-Type': 'application/json' 257 | } 258 | } 259 | ); 260 | 261 | const result = response.data.choices[0].message; 262 | return { 263 | content: [{ 264 | type: 'text', 265 | text: result.content, 266 | ...(result.reasoning_content && { metadata: { reasoning: result.reasoning_content } }) 267 | }] 268 | }; 269 | } catch (error) { 270 | const axiosError = error as AxiosError; 271 | if (axiosError.response) { 272 | throw new McpError( 273 | ErrorCode.InvalidRequest, 274 | `DeepSeek API error: ${axiosError.response.status} ${axiosError.response.statusText}` 275 | ); 276 | } 277 | throw error; 278 | } 279 | } 280 | ); 281 | 282 | server.tool( 283 | 'configure', 284 | { instruction: z.string() }, 285 | async ({ instruction }: { instruction: string }) => { 286 | try { 287 | const newConfig = await interpretConfigInstruction(instruction); 288 | modelConfig = ConfigSchema.parse(newConfig); 289 | return { 290 | content: [{ 291 | type: 'text', 292 | text: `Configuration updated:\n${JSON.stringify(modelConfig, null, 2)}` 293 | }] 294 | }; 295 | } catch (error) { 296 | return { 297 | content: [{ 298 | type: 'text', 299 | text: `Configuration error: ${error instanceof Error ? error.message : String(error)}` 300 | }], 301 | error: new McpError(ErrorCode.InvalidRequest, 'Invalid configuration instruction') 302 | }; 303 | } 304 | } 305 | ); 306 | 307 | server.tool( 308 | 'multi-round-chat', 309 | { 310 | messages: z.array(MessageSchema), 311 | temperature: z.number().optional(), 312 | shouldSummarize: z.boolean().optional() 313 | }, 314 | async ({ messages, temperature, shouldSummarize = false }) => { 315 | try { 316 | const isReasoner = modelConfig.model?.includes('reasoner'); 317 | 318 | if (shouldSummarize) { 319 | const summaryResponse = await axios.post( 320 | 'https://api.deepseek.com/v1/chat/completions', 321 | { 322 | messages: [...messages, { 323 | role: 'user', 324 | content: { 325 | type: 'text', 326 | text: 'Please summarize our conversation into key points needed for continuing the discussion.' 327 | } 328 | }], 329 | model: modelConfig.model, 330 | temperature: 0.3, 331 | max_tokens: modelConfig.max_tokens 332 | }, 333 | { 334 | headers: { 335 | 'Authorization': `Bearer ${DEEPSEEK_API_KEY}`, 336 | 'Content-Type': 'application/json' 337 | } 338 | } 339 | ); 340 | 341 | const summary = summaryResponse.data.choices[0].message; 342 | return { 343 | content: [{ 344 | type: 'text', 345 | text: summary.content, 346 | ...(summary.reasoning_content && { metadata: { reasoning: summary.reasoning_content } }) 347 | }] 348 | }; 349 | } 350 | 351 | const payload: Record = { 352 | messages, 353 | model: modelConfig.model, 354 | max_tokens: modelConfig.max_tokens 355 | }; 356 | 357 | if (!isReasoner) { 358 | payload.temperature = temperature ?? modelConfig.temperature; 359 | } 360 | 361 | const response = await axios.post( 362 | 'https://api.deepseek.com/v1/chat/completions', 363 | payload, 364 | { 365 | headers: { 366 | 'Authorization': `Bearer ${DEEPSEEK_API_KEY}`, 367 | 'Content-Type': 'application/json' 368 | } 369 | } 370 | ); 371 | 372 | const result = response.data.choices[0].message; 373 | return { 374 | content: [{ 375 | type: 'text', 376 | text: result.content, 377 | ...(result.reasoning_content && { metadata: { reasoning: result.reasoning_content } }) 378 | }] 379 | }; 380 | } catch (error) { 381 | const axiosError = error as AxiosError; 382 | if (axiosError.response) { 383 | throw new McpError( 384 | ErrorCode.InvalidRequest, 385 | `API error: ${JSON.stringify(axiosError.response.data)}` 386 | ); 387 | } 388 | throw new McpError(ErrorCode.InternalError, 'Failed to process chat request'); 389 | } 390 | } 391 | ); 392 | 393 | server.tool( 394 | 'continue-conversation', 395 | { 396 | previousMessages: z.array(MessageSchema), 397 | newQuestion: z.string(), 398 | shouldSummarize: z.boolean().optional() 399 | }, 400 | async ({ previousMessages, newQuestion, shouldSummarize = false }) => { 401 | try { 402 | if (shouldSummarize) { 403 | const summaryResponse = await axios.post( 404 | 'https://api.deepseek.com/v1/chat/completions', 405 | { 406 | messages: [ 407 | ...previousMessages, 408 | { 409 | role: 'user', 410 | content: { 411 | type: 'text', 412 | text: 'Please summarize our conversation so far into key points.' 413 | } 414 | } 415 | ], 416 | model: modelConfig.model, 417 | temperature: 0.3 418 | }, 419 | { 420 | headers: { 421 | 'Authorization': `Bearer ${DEEPSEEK_API_KEY}`, 422 | 'Content-Type': 'application/json' 423 | } 424 | } 425 | ); 426 | 427 | const summary = summaryResponse.data.choices[0].message; 428 | return { 429 | content: [{ 430 | type: 'text', 431 | text: `Previous conversation summary: ${summary.content}` 432 | }] 433 | }; 434 | } 435 | 436 | const response = await axios.post( 437 | 'https://api.deepseek.com/v1/chat/completions', 438 | { 439 | messages: [...previousMessages, { role: 'user', content: { type: 'text', text: newQuestion } }], 440 | model: modelConfig.model, 441 | temperature: modelConfig.temperature 442 | }, 443 | { 444 | headers: { 445 | 'Authorization': `Bearer ${DEEPSEEK_API_KEY}`, 446 | 'Content-Type': 'application/json' 447 | } 448 | } 449 | ); 450 | 451 | const result = response.data.choices[0].message; 452 | return { 453 | content: [{ 454 | type: 'text', 455 | text: result.content 456 | }] 457 | }; 458 | } catch (error) { 459 | const axiosError = error as AxiosError; 460 | if (axiosError.response) { 461 | throw new McpError( 462 | ErrorCode.InvalidRequest, 463 | `API error: ${JSON.stringify(axiosError.response.data)}` 464 | ); 465 | } 466 | throw new McpError(ErrorCode.InternalError, 'Failed to process conversation'); 467 | } 468 | } 469 | ); 470 | 471 | // 3. Register PROMPTS last (they're templates for LLM interaction) 472 | server.prompt( 473 | 'system', // Handler for system prompts 474 | { 475 | content: z.string(), 476 | temperature: z.number().optional(), 477 | stop: z.array(z.string()).optional() 478 | }, 479 | async ({ content, temperature, stop }) => { 480 | const messages = [{ 481 | role: 'system', 482 | content: { type: 'text', text: content } 483 | }]; 484 | 485 | return { messages, stop }; 486 | } 487 | ); 488 | 489 | server.prompt( 490 | 'chat', // Handler for chat interactions 491 | { 492 | content: z.string(), 493 | history: z.array(MessageSchema).optional(), 494 | temperature: z.number().optional(), 495 | shouldSummarize: z.boolean().optional(), 496 | stop: z.array(z.string()).optional() 497 | }, 498 | async ({ content, history = [], temperature, shouldSummarize = false, stop }) => { 499 | try { 500 | const messages = [ 501 | ...history, 502 | { 503 | role: 'user', 504 | content: { type: 'text', text: content } 505 | } 506 | ]; 507 | 508 | if (shouldSummarize) { 509 | messages.push({ 510 | role: 'user', 511 | content: { 512 | type: 'text', 513 | text: 'Please summarize our conversation into key points needed for continuing the discussion.' 514 | } 515 | }); 516 | } 517 | 518 | return { 519 | messages, 520 | temperature: temperature ?? modelConfig.temperature, 521 | stop 522 | }; 523 | } catch (error) { 524 | throw new McpError( 525 | ErrorCode.InternalError, 526 | `Failed to process chat prompt: ${error instanceof Error ? error.message : String(error)}` 527 | ); 528 | } 529 | } 530 | ); 531 | 532 | server.prompt( 533 | 'chat', // Handler for chat interactions 534 | { 535 | content: z.string(), 536 | history: z.array(MessageSchema).optional(), 537 | temperature: z.number().optional(), 538 | shouldSummarize: z.boolean().optional(), 539 | stop: z.array(z.string()).optional() 540 | }, 541 | async ({ type, content, messages = [], temperature, shouldSummarize = false, stopSequences }) => { 542 | try { 543 | const isReasoner = modelConfig.model?.includes('reasoner'); 544 | 545 | // Handle system prompts 546 | if (type === 'system') { 547 | return { 548 | messages: [{ 549 | role: 'system', 550 | content // Content is already in the right format 551 | }], 552 | stop: stopSequences 553 | }; 554 | } 555 | 556 | // Handle chat interactions 557 | if (shouldSummarize) { 558 | const summaryResponse = await axios.post( 559 | 'https://api.deepseek.com/v1/chat/completions', 560 | { 561 | messages: [...messages, { 562 | role: 'user', 563 | content: { 564 | type: 'text', 565 | text: 'Please summarize our conversation into key points needed for continuing the discussion.' 566 | } 567 | }], 568 | model: modelConfig.model, 569 | temperature: 0.3, 570 | max_tokens: modelConfig.max_tokens 571 | }, 572 | { 573 | headers: { 574 | 'Authorization': `Bearer ${DEEPSEEK_API_KEY}`, 575 | 'Content-Type': 'application/json' 576 | } 577 | } 578 | ); 579 | 580 | const summary = summaryResponse.data.choices[0].message; 581 | return { 582 | content: [{ 583 | type: 'text', 584 | text: summary.content, 585 | ...(summary.reasoning_content && { metadata: { reasoning: summary.reasoning_content } }) 586 | }] 587 | }; 588 | } 589 | 590 | const payload: Record = { 591 | messages: [...messages, { role: 'user', content }], // Content is already in the right format 592 | model: modelConfig.model, 593 | max_tokens: modelConfig.max_tokens 594 | }; 595 | 596 | if (!isReasoner) { 597 | payload.temperature = temperature ?? modelConfig.temperature; 598 | } 599 | 600 | const response = await axios.post( 601 | 'https://api.deepseek.com/v1/chat/completions', 602 | payload, 603 | { 604 | headers: { 605 | 'Authorization': `Bearer ${DEEPSEEK_API_KEY}`, 606 | 'Content-Type': 'application/json' 607 | } 608 | } 609 | ); 610 | 611 | const result = response.data.choices[0].message; 612 | return { 613 | content: [{ 614 | type: 'text', 615 | text: result.content, 616 | ...(result.reasoning_content && { metadata: { reasoning: result.reasoning_content } }) 617 | }] 618 | }; 619 | } catch (error) { 620 | const axiosError = error as AxiosError; 621 | if (axiosError.response) { 622 | throw new McpError( 623 | ErrorCode.InvalidRequest, 624 | `API error: ${JSON.stringify(axiosError.response.data)}` 625 | ); 626 | } 627 | throw new McpError(ErrorCode.InternalError, 'Failed to process request'); 628 | } 629 | } 630 | ); 631 | 632 | // Configure Transport 633 | const transport = new StdioServerTransport(); 634 | 635 | // Error Handling 636 | process.on('uncaughtException', (error: Error) => { 637 | process.stderr.write(`Uncaught exception: ${error.stack ?? error.message}\n`); 638 | process.exit(1); 639 | }); 640 | 641 | process.on('unhandledRejection', (reason: unknown) => { 642 | process.stderr.write(`Unhandled rejection: ${reason instanceof Error ? reason.stack : String(reason)}\n`); 643 | process.exit(1); 644 | }); 645 | 646 | // Initialize prompt templates 647 | const systemTemplate = { 648 | type: 'system', 649 | content: { 650 | type: 'text' as const, 651 | text: '' 652 | } 653 | }; 654 | 655 | const chatTemplate = { 656 | type: 'chat', 657 | content: { 658 | type: 'text' as const, 659 | text: '' 660 | }, 661 | messages: [] 662 | }; 663 | 664 | // Set up prompt templates before connecting 665 | server.setPromptTemplates({ 666 | system: systemTemplate, 667 | chat: chatTemplate 668 | }); 669 | 670 | // Connect server 671 | server.connect(transport).catch((error: Error) => { 672 | process.stderr.write(`Transport error: ${error.stack ?? error.message}\n`); 673 | process.exit(1); 674 | }); -------------------------------------------------------------------------------- /package-lock.json: -------------------------------------------------------------------------------- 1 | { 2 | "name": "deepseek-mcp-server", 3 | "version": "0.2.1", 4 | "lockfileVersion": 3, 5 | "requires": true, 6 | "packages": { 7 | "": { 8 | "name": "deepseek-mcp-server", 9 | "version": "0.2.1", 10 | "license": "MIT", 11 | 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"https://github.com/sponsors/colinhacks" 1220 | } 1221 | }, 1222 | "node_modules/zod-to-json-schema": { 1223 | "version": "3.24.5", 1224 | "resolved": "https://registry.npmjs.org/zod-to-json-schema/-/zod-to-json-schema-3.24.5.tgz", 1225 | "integrity": "sha512-/AuWwMP+YqiPbsJx5D6TfgRTc4kTLjsh5SOcd4bLsfUg2RcEXrFMJl1DGgdHy2aCfsIA/cr/1JM0xcB2GZji8g==", 1226 | "license": "ISC", 1227 | "peerDependencies": { 1228 | "zod": "^3.24.1" 1229 | } 1230 | } 1231 | } 1232 | } 1233 | -------------------------------------------------------------------------------- /package.json: -------------------------------------------------------------------------------- 1 | { 2 | "name": "deepseek-mcp-server", 3 | "version": "1.2.0", 4 | "description": "Model Context Protocol server for DeepSeek's advanced language models.", 5 | "type": "module", 6 | "main": "build/index.js", 7 | "bin": { 8 | "deepseek-mcp-server": "./build/index.js" 9 | }, 10 | "files": [ 11 | "build/**/*", 12 | "assets/favicon.ico", 13 | "assets/favicon-32x32.png", 14 | "assets/apple-touch-icon.png" 15 | ], 16 | "scripts": { 17 | "build": "tsc", 18 | "start": "node build/index.js", 19 | "prepublishOnly": "npm run build", 20 | "inspect": "npx @modelcontextprotocol/inspector build/index.js" 21 | }, 22 | "dependencies": { 23 | "@modelcontextprotocol/sdk": "^1.12.1", 24 | "axios": "^1.6.0", 25 | "dotenv": "^16.3.1" 26 | }, 27 | "devDependencies": { 28 | "@types/node": "^20.19.0", 29 | "typescript": "^5.2.2" 30 | }, 31 | "author": "DMontgomery40", 32 | "license": "MIT", 33 | "repository": { 34 | "type": "git", 35 | "url": "https://github.com/DMontgomery40/deepseek-mcp-server" 36 | }, 37 | "keywords": [ 38 | "mcp", 39 | "deepseek", 40 | "ai", 41 | "llm" 42 | ] 43 | } 44 | -------------------------------------------------------------------------------- /smithery.yaml: -------------------------------------------------------------------------------- 1 | # Smithery configuration file: https://smithery.ai/docs/config#smitheryyaml 2 | 3 | startCommand: 4 | type: stdio 5 | configSchema: 6 | # JSON Schema defining the configuration options for the MCP. 7 | type: object 8 | required: 9 | - deepseekApiKey 10 | properties: 11 | deepseekApiKey: 12 | type: string 13 | description: The API key for the DeepSeek server. 14 | commandFunction: 15 | # A function that produces the CLI command to start the MCP on stdio. 16 | |- 17 | (config) => ({ command: 'node', args: ['build/index.js'], env: { DEEPSEEK_API_KEY: config.deepseekApiKey } }) -------------------------------------------------------------------------------- /src/docs/deepseek-api-example.md: -------------------------------------------------------------------------------- 1 | Reasoning Model (deepseek-reasoner) 2 | deepseek-reasoner is a reasoning model developed by DeepSeek. Before delivering the final answer, the model first generates a Chain of Thought (CoT) to enhance the accuracy of its responses. Our API provides users with access to the CoT content generated by deepseek-reasoner, enabling them to view, display, and distill it. 3 | 4 | When using deepseek-reasoner, please upgrade the OpenAI SDK first to support the new parameters. 5 | 6 | pip3 install -U openai 7 | 8 | API Parameters 9 | Input： 10 | 11 | max_tokens：The maximum length of the final response after the CoT output is completed, defaulting to 4K, with a maximum of 8K. Note that the CoT output can reach up to 32K tokens, and the parameter to control the CoT length (reasoning_effort) will be available soon. 12 | Output： 13 | 14 | reasoning_content：The content of the CoT，which is at the same level as content in the output structure. See API Example for details 15 | contentThe content of the final answer 16 | Context Length：The API supports a maximum context length of 64K, and the length of the output reasoning_content is not counted within the 64K context length. 17 | 18 | Supported Features：Chat Completion、Chat Prefix Completion (Beta) 19 | 20 | Not Supported Features：Function Call、Json Output、FIM (Beta) 21 | 22 | Not Supported Parameters：temperature、top_p、presence_penalty、frequency_penalty、logprobs、top_logprobs. Please note that to ensure compatibility with existing software, setting these parameters will not trigger an error but will also have no effect. 23 | 24 | Multi-round Conversation 25 | In each round of the conversation, the model outputs the CoT (reasoning_content) and the final answer (content). In the next round of the conversation, the CoT from previous rounds is not concatenated into the context, as illustrated in the following diagram: 26 | 27 | 28 | Please note that if the reasoning_content field is included in the sequence of input messages, the API will return a 400 error. Therefore, you should remove the reasoning_content field from the API response before making the API request, as demonstrated in the API example. 29 | 30 | API Example 31 | The following code, using Python as an example, demonstrates how to access the CoT and the final answer, as well as how to conduct multi-round conversations: 32 | 33 | NoStreaming 34 | Streaming 35 | from openai import OpenAI 36 | client = OpenAI(api_key="", base_url="https://api.deepseek.com") 37 | 38 | # Round 1 39 | messages = [{"role": "user", "content": "9.11 and 9.8, which is greater?"}] 40 | response = client.chat.completions.create( 41 | model="deepseek-reasoner", 42 | messages=messages 43 | ) 44 | 45 | reasoning_content = response.choices[0].message.reasoning_content 46 | content = response.choices[0].message.content 47 | 48 | # Round 2 49 | messages.append({'role': 'assistant', 'content': content}) 50 | messages.append({'role': 'user', 'content': "How many Rs are there in the word 'strawberry'?"}) 51 | response = client.chat.completions.create( 52 | model="deepseek-reasoner", 53 | messages=messages 54 | ) 55 | # ... 56 | 57 | 58 | Previous 59 | Get User Balance 60 | Next 61 | Multi-round Conversation 62 | API Parameters 63 | Multi-round Conversation 64 | API Example -------------------------------------------------------------------------------- /src/index.ts: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env node 2 | // NOTE: Ensure @modelcontextprotocol/sdk is installed for the following import to work 3 | import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js"; 4 | import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js"; 5 | import { 6 | ListPromptsRequestSchema, 7 | GetPromptRequestSchema, 8 | ErrorCode, 9 | McpError 10 | } from "@modelcontextprotocol/sdk/types.js"; 11 | import axios from "axios"; 12 | import dotenv from "dotenv"; 13 | import { DeepSeekResponse, ChatMessage } from "./types"; 14 | import { z } from "zod"; 15 | 16 | // Load environment variables 17 | dotenv.config(); 18 | const DEEPSEEK_API_KEY = process.env.DEEPSEEK_API_KEY; 19 | if (!DEEPSEEK_API_KEY) throw new McpError(ErrorCode.InvalidRequest, "Missing DEEPSEEK_API_KEY"); 20 | 21 | // Define prompt templates for protocol compliance 22 | const PROMPTS = { 23 | system: { 24 | name: "system", 25 | description: "Set system behavior for the AI", 26 | arguments: [ 27 | { name: "content", description: "System instruction", required: true } 28 | ] 29 | }, 30 | chat: { 31 | name: "chat", 32 | description: "Chat with the AI", 33 | arguments: [ 34 | { name: "message", description: "User message", required: true }, 35 | { name: "temperature", description: "Response temperature (0-1)", required: false } 36 | ] 37 | } 38 | }; 39 | 40 | const server = new McpServer({ 41 | name: "deepseek-mcp-server", 42 | version: "1.1.0" 43 | }); 44 | 45 | // Register prompt templates using server.prompt() 46 | server.prompt( 47 | "system", 48 | { content: z.string() }, 49 | async ({ content }: { content: string }) => { 50 | return { 51 | messages: [ 52 | { 53 | role: "user", 54 | content: { 55 | type: "text", 56 | text: `[System Instruction]\n${content}` 57 | } 58 | } 59 | ] 60 | }; 61 | } 62 | ); 63 | 64 | server.prompt( 65 | "chat", 66 | { message: z.string(), temperature: z.string().optional() }, 67 | async ({ message, temperature }: { message: string; temperature?: string }) => { 68 | return { 69 | messages: [ 70 | { 71 | role: "user", 72 | content: { 73 | type: "text", 74 | text: message 75 | } 76 | } 77 | ], 78 | temperature 79 | }; 80 | } 81 | ); 82 | 83 | // Register prompts/list handler 84 | server.server.setRequestHandler(ListPromptsRequestSchema, async () => ({ 85 | prompts: Object.values(PROMPTS) 86 | })); 87 | 88 | // Register prompts/get handler 89 | server.server.setRequestHandler(GetPromptRequestSchema, async (request: any) => { 90 | const prompt = PROMPTS[request.params.name as keyof typeof PROMPTS]; 91 | if (!prompt) { 92 | throw new McpError(ErrorCode.InvalidRequest, `Prompt not found: ${request.params.name}`); 93 | } 94 | if (request.params.name === "system") { 95 | return { 96 | messages: [{ 97 | role: "user", 98 | content: { 99 | type: "text", 100 | text: `[System Instruction]\n${request.params.arguments?.content ?? ""}` 101 | } 102 | }] 103 | }; 104 | } 105 | if (request.params.name === "chat") { 106 | return { 107 | messages: [{ 108 | role: "user", 109 | content: { 110 | type: "text", 111 | text: request.params.arguments?.message ?? "" 112 | } 113 | }], 114 | temperature: request.params.arguments?.temperature 115 | }; 116 | } 117 | throw new McpError(ErrorCode.InvalidRequest, "Unknown prompt type"); 118 | }); 119 | 120 | // Example: Register a chat-completion tool (update as needed) 121 | server.tool( 122 | "chat_completion", 123 | { 124 | message: { type: "string", optional: true }, 125 | messages: { type: "array", items: { type: "object" }, optional: true }, 126 | model: { type: "string", default: "deepseek-chat" }, 127 | temperature: { type: "number", default: 0.7 }, 128 | max_tokens: { type: "number", default: 8000 }, 129 | top_p: { type: "number", default: 1.0 }, 130 | frequency_penalty: { type: "number", default: 0.1 }, 131 | presence_penalty: { type: "number", default: 0 }, 132 | reasoning_content: { type: "string", optional: true }, 133 | stream: { type: "boolean", default: false } 134 | }, 135 | async (args: any) => { 136 | let messages: ChatMessage[]; 137 | if (args.message) { 138 | messages = [{ role: 'user', content: args.message }]; 139 | } else if (args.messages) { 140 | messages = args.messages; 141 | } else { 142 | throw new McpError(ErrorCode.InvalidRequest, "Either 'message' or 'messages' must be provided"); 143 | } 144 | try { 145 | const response = await axios.post( 146 | "https://api.deepseek.com/chat/completions", 147 | { 148 | messages, 149 | model: args.model, 150 | temperature: args.temperature, 151 | max_tokens: args.max_tokens, 152 | top_p: args.top_p, 153 | frequency_penalty: args.frequency_penalty, 154 | presence_penalty: args.presence_penalty, 155 | reasoning_content: args.reasoning_content, 156 | stream: args.stream 157 | }, 158 | { 159 | headers: { 160 | 'Authorization': `Bearer ${DEEPSEEK_API_KEY}`, 161 | 'Content-Type': 'application/json' 162 | } 163 | } 164 | ); 165 | return { 166 | content: [{ 167 | type: "text", 168 | text: response.data.choices[0].message.content 169 | }] 170 | }; 171 | } catch (error: any) { 172 | throw new McpError(ErrorCode.InternalError, error.message); 173 | } 174 | } 175 | ); 176 | 177 | async function main() { 178 | const transport = new StdioServerTransport(); 179 | await server.connect(transport); 180 | console.error("DeepSeek MCP server running on stdio"); 181 | } 182 | 183 | main().catch(console.error); -------------------------------------------------------------------------------- /src/types.ts: -------------------------------------------------------------------------------- 1 | export interface DeepSeekResponse { 2 | id: string; 3 | object: string; 4 | created: number; 5 | model: string; 6 | choices: Array<{ 7 | index: number; 8 | message: { 9 | role: 'assistant'; 10 | content: string; 11 | reasoning_content?: string; 12 | }; 13 | delta?: { 14 | content?: string; 15 | reasoning_content?: string; 16 | }; 17 | finish_reason: 'stop' | 'length' | 'content_filter'; 18 | }>; 19 | usage: { 20 | prompt_tokens: number; 21 | completion_tokens: number; 22 | total_tokens: number; 23 | }; 24 | } 25 | 26 | export interface Prompt { 27 | content: string; 28 | type: 'system' | 'user' | 'assistant'; 29 | reasoning?: boolean; 30 | temperature?: number; 31 | stop_sequences?: string[]; 32 | } 33 | 34 | export interface ChatMessage { 35 | role: 'system' | 'user' | 'assistant'; 36 | content: string; 37 | reasoning_content?: string; 38 | } 39 | 40 | export interface ChatCompletionArgs { 41 | message?: string; 42 | messages?: ChatMessage[]; 43 | model?: string; 44 | temperature?: number; 45 | max_tokens?: number; 46 | top_p?: number; 47 | frequency_penalty?: number; 48 | presence_penalty?: number; 49 | reasoning_content?: string; 50 | stream?: boolean; 51 | } 52 | 53 | // Type guard for chat completion arguments 54 | export interface ModelInfo { 55 | id: string; 56 | name: string; 57 | description: string; 58 | } 59 | 60 | export interface ModelConfig { 61 | id: string; 62 | name: string; 63 | type: 'number' | 'integer' | 'string' | 'boolean'; 64 | description: string; 65 | default?: any; 66 | minimum?: number; 67 | maximum?: number; 68 | } 69 | 70 | export function isValidChatCompletionArgs(args: unknown): args is ChatCompletionArgs { 71 | if (!args || typeof args !== 'object') { 72 | return false; 73 | } 74 | 75 | const { message, messages, model, temperature, max_tokens, top_p, frequency_penalty, presence_penalty, reasoning_content, stream } = args as ChatCompletionArgs; 76 | 77 | // Must have either message or messages 78 | if (!message && !messages) { 79 | return false; 80 | } 81 | 82 | // If message is provided, it must be a string 83 | if (message !== undefined && typeof message !== 'string') { 84 | return false; 85 | } 86 | 87 | // If messages is provided, validate the array 88 | if (messages !== undefined) { 89 | if (!Array.isArray(messages)) { 90 | return false; 91 | } 92 | 93 | const validRoles = ['system', 'user', 'assistant'] as const; 94 | const isValidMessage = (msg: unknown): msg is ChatMessage => { 95 | if (!msg || typeof msg !== 'object') { 96 | return false; 97 | } 98 | const { role, content } = msg as ChatMessage; 99 | return ( 100 | validRoles.includes(role as typeof validRoles[number]) && 101 | typeof content === 'string' 102 | ); 103 | }; 104 | 105 | if (!messages.every(isValidMessage)) { 106 | return false; 107 | } 108 | } 109 | 110 | if (model !== undefined && typeof model !== 'string') { 111 | return false; 112 | } 113 | 114 | if (temperature !== undefined && (typeof temperature !== 'number' || temperature < 0 || temperature > 2)) { 115 | return false; 116 | } 117 | 118 | if (max_tokens !== undefined && (typeof max_tokens !== 'number' || max_tokens < 1)) { 119 | return false; 120 | } 121 | 122 | if (top_p !== undefined && (typeof top_p !== 'number' || top_p < 0 || top_p > 1)) { 123 | return false; 124 | } 125 | 126 | if (frequency_penalty !== undefined && (typeof frequency_penalty !== 'number' || frequency_penalty < -2 || frequency_penalty > 2)) { 127 | return false; 128 | } 129 | 130 | if (presence_penalty !== undefined && (typeof presence_penalty !== 'number' || presence_penalty < -2 || presence_penalty > 2)) { 131 | return false; 132 | } 133 | 134 | if (reasoning_content !== undefined && typeof reasoning_content !== 'string') { 135 | return false; 136 | } 137 | 138 | if (stream !== undefined && typeof stream !== 'boolean') { 139 | return false; 140 | } 141 | 142 | return true; 143 | } 144 | -------------------------------------------------------------------------------- /tsconfig.json: -------------------------------------------------------------------------------- 1 | { 2 | "compilerOptions": { 3 | "target": "ES2020", 4 | "module": "ES2020", 5 | "moduleResolution": "node", 6 | "outDir": "./build", 7 | "rootDir": "./src", 8 | "strict": true, 9 | "esModuleInterop": true, 10 | "skipLibCheck": true, 11 | "forceConsistentCasingInFileNames": true 12 | }, 13 | "include": ["src/**/*"], 14 | "exclude": ["node_modules"] 15 | } 16 | -------------------------------------------------------------------------------- /util.ts: -------------------------------------------------------------------------------- 1 | import { z } from 'zod'; 2 | import { McpError, ErrorCode } from '@modelcontextprotocol/sdk/types.js'; 3 | 4 | export const ConfigSchema = z.object({ 5 | model: z.string() 6 | .default('deepseek-chat') 7 | .describe('Model identifier for DeepSeek API'), 8 | temperature: z.number() 9 | .min(0) 10 | .max(2) 11 | .default(0.7) 12 | .describe('Controls randomness in generation'), 13 | max_tokens: z.number() 14 | .min(1) 15 | .max(8000) 16 | .default(8000) 17 | .describe('Maximum tokens to generate'), 18 | top_p: z.number() 19 | .min(0) 20 | .max(1) 21 | .default(1) 22 | .describe('Nucleus sampling threshold'), 23 | }); 24 | 25 | export type ModelConfig = z.infer; 26 | 27 | export async function interpretConfigInstruction( 28 | instruction: string 29 | ): Promise { 30 | const config: ModelConfig = { 31 | model: 'deepseek-chat', 32 | temperature: 0.7, 33 | max_tokens: 8000, 34 | top_p: 1 35 | }; 36 | 37 | const normalizedInstruction = instruction.toLowerCase(); 38 | 39 | // Model selection 40 | if (normalizedInstruction.includes('reason')) { 41 | config.model = 'deepseek-reasoner'; 42 | } else if (normalizedInstruction.includes('chat')) { 43 | config.model = 'deepseek-chat'; 44 | } 45 | 46 | // Temperature parsing 47 | const tempMatch = normalizedInstruction.match(/temperature[:\s]+(\d*\.?\d+)/); 48 | if (tempMatch) { 49 | const temp = parseFloat(tempMatch[1]); 50 | if (!isNaN(temp) && temp >= 0 && temp <= 2) { 51 | config.temperature = temp; 52 | } else { 53 | throw new McpError( 54 | ErrorCode.InvalidRequest, 55 | 'Temperature must be between 0 and 2' 56 | ); 57 | } 58 | } else if (normalizedInstruction.includes('high') || normalizedInstruction.includes('creative')) { 59 | config.temperature = 0.8; 60 | } else if (normalizedInstruction.includes('low') || normalizedInstruction.includes('precise')) { 61 | config.temperature = 0.2; 62 | } 63 | 64 | // Token length parsing 65 | const tokenMatch = normalizedInstruction.match(/(\d+)\s*(tokens|length)/); 66 | if (tokenMatch) { 67 | const tokens = parseInt(tokenMatch[1]); 68 | if (!isNaN(tokens) && tokens > 0) { 69 | config.max_tokens = Math.min(8000, tokens); 70 | } else { 71 | throw new McpError( 72 | ErrorCode.InvalidRequest, 73 | 'Token length must be a positive number' 74 | ); 75 | } 76 | } 77 | 78 | // Top-p parsing 79 | const topPMatch = normalizedInstruction.match(/top[_\s-]?p[:\s]+(\d*\.?\d+)/); 80 | if (topPMatch) { 81 | const topP = parseFloat(topPMatch[1]); 82 | if (!isNaN(topP) && topP >= 0 && topP <= 1) { 83 | config.top_p = topP; 84 | } else { 85 | throw new McpError( 86 | ErrorCode.InvalidRequest, 87 | 'Top-p must be between 0 and 1' 88 | ); 89 | } 90 | } 91 | 92 | try { 93 | return ConfigSchema.parse(config); 94 | } catch (error) { 95 | throw new McpError( 96 | ErrorCode.InvalidRequest, 97 | 'Invalid configuration parameters generated from instruction' 98 | ); 99 | } 100 | } --------------------------------------------------------------------------------