├── .gitignore ├── .python-version ├── LICENSE ├── README.md ├── images ├── bind_app.png ├── create_workflow.png ├── debug_workflow.png └── publish_workflow.png ├── poetry.lock ├── pyproject.toml ├── src ├── mcp_server │ ├── __init__.py │ ├── entities │ │ ├── flow.py │ │ └── ifly_client.py │ └── server.py └── test │ ├── __init__.py │ ├── pytest.ini │ ├── test_ifly_api.py │ └── test_server.py └── uv.lock /.gitignore: -------------------------------------------------------------------------------- 1 | # Python-generated files 2 | __pycache__/ 3 | *.py[oc] 4 | build/ 5 | dist/ 6 | wheels/ 7 | *.egg-info 8 | 9 | # Virtual environments 10 | .venv 11 | 12 | # custom 13 | .vscode 14 | config.yaml 15 | .idea -------------------------------------------------------------------------------- /.python-version: -------------------------------------------------------------------------------- 1 | 3.11.11 2 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2025 iFLYTEK 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 |

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5 | The fastest way to build workflows with an AI agent platform! 6 |

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8 | 9 | License 10 | | 11 | 12 | Docs 13 | | 14 | 15 | Homepage 16 | 17 |

18 | 19 | # iFlytek Workflow MCP Server 20 | 21 | [The Model Context Protocol (MCP)](https://modelcontextprotocol.io/introduction) is an open protocol designed for effortless integration between LLM applications and external data sources or tools, offering a standardized framework to seamlessly provide LLMs with the context they require. 22 | 23 | This a simple implementation of an MCP server using iFlytek. It enables calling iFlytek workflows through MCP tools. 24 | 25 | ## Features 26 | 27 | ### Functional Overview 28 | 29 | This system is built on the iFlytek MCP server and enables intelligent workflow scheduling, making it suitable for various business scenarios. 30 | 31 | - **Workflow Structure**: Composed of multiple nodes, supporting 14 types of nodes (including basic, tool, logic, and transformation types). 32 | - **Core Components**: By default, the workflow includes a **Start Node** (user input) and an **End Node** (output result). 33 | - **Execution Mode**: Once triggered, the workflow executes automatically according to predefined sequences and rules, requiring no manual intervention. 34 | 35 | ### Core Capabilities 36 | 37 | #### **Robust Node Support** 38 | 39 | - 14 types of workflow nodes to meet diverse business requirements. 40 | - Supports **complex variable I/O**, enabling flexible data transmission. 41 | 42 | #### **Advanced Orchestration Modes** 43 | 44 | - **Sequential Execution**: Tasks execute one after another in order. 45 | - **Parallel Execution**: Multiple tasks run simultaneously to enhance efficiency. 46 | - **Loop Execution**: Supports iterative loops for handling repetitive tasks. 47 | - **Nested Execution**: Allows embedding sub-workflows within workflows, improving reusability. 48 | - Utilizes the **Hook Mechanism** to enable **streaming output**, ensuring real-time processing. 49 | 50 | #### **Multiple Development Paradigms** 51 | 52 | - **Single-turn, single-branch**: Linear execution of simple tasks. 53 | - **Single-turn, multi-branch**: Supports branching logic to handle complex processes. 54 | - **Single-turn loop**: Manages looped tasks to enhance automation. 55 | - **Multi-turn interaction**: Supports context memory for dynamic conversations. 56 | 57 | ### Capability Expansion 58 | 59 | - **Multi-Model Support**: Based on the **Model of Models (MoM)** hybrid application architecture, providing multiple model choices at critical workflow stages. This allows for flexible model combinations, improving task adaptability. 60 | 61 | 62 | 63 | ## Usage with MCP client 64 | 65 | ### Prepare config.yaml 66 | 67 | Before using the mcp server, you should prepare a config.yaml to save your workflow info. The example config like this: 68 | 69 | ```yaml 70 | - flow_id: 'flow id' # required 71 | name: 'flow name' # optional, if not set, obtain the name from the cloud. 72 | description: 'flow description' # optional, if not set, obtain the description from the cloud. 73 | api_key: 'API Key:API Secret' # required 74 | ``` 75 | 76 | #### Get workflow authentication information 77 | 1. [Create a bot](https://xinghuo.xfyun.cn/botcenter/createbot) 78 | ![](./images/create_workflow.png) 79 | 80 | 2. Publish a workflow 81 | - **Step 1.** Debug the workflow you just created. 82 | - **Step 2.** Engage in a conversation with your workflow and ensure the conversation is successful. 83 | - **Step 3.** You can now click the publish button. 84 | ![](./images/debug_workflow.png) 85 | - **Step 4.** Select "Publish as API" and click the "Configure" button. 86 | ![](./images/publish_workflow.png) 87 | - **Step 5.** Select the application you need to bind and bind it. Now you can retrieve the corresponding workflow ID and authentication information. Enjoy! 88 | ![](./images/bind_app.png) 89 | > **Note**: If you find that you are unable to select an app, you can go to https://www.xfyun.cn to apply. 90 | ### Manual Installation 91 | 92 | To add a persistent client, add the following to your `claude_desktop_config.json` or `mcp.json` file: 93 | 94 | ```json 95 | { 96 | "mcpServers": { 97 | "ifly-workflow-mcp-server": { 98 | "command": "uvx", 99 | "args": [ 100 | "--from", 101 | "git+https://github.com/iflytek/ifly-workflow-mcp-server", 102 | "ifly_workflow_mcp_server" 103 | ], 104 | "env": { 105 | "CONFIG_PATH": "$CONFIG_PATH" 106 | } 107 | } 108 | } 109 | } 110 | ``` 111 | 112 | 113 | 114 | Example config: 115 | 116 | ```json 117 | { 118 | "mcpServers": { 119 | "ifly-workflow-mcp-server": { 120 | "command": "uvx", 121 | "args": [ 122 | "--from", 123 | "git+https://github.com/iflytek/ifly-workflow-mcp-server", 124 | "ifly_workflow_mcp_server" 125 | ], 126 | "env": { 127 | "CONFIG_PATH": "/Users/hygao1024/Projects/config.yaml" 128 | } 129 | } 130 | } 131 | } 132 | ``` 133 | 134 | 135 | -------------------------------------------------------------------------------- /images/bind_app.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/iflytek/ifly-workflow-mcp-server/8926620b3e8c0c1245cc46acf011dd6d432ca30d/images/bind_app.png -------------------------------------------------------------------------------- /images/create_workflow.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/iflytek/ifly-workflow-mcp-server/8926620b3e8c0c1245cc46acf011dd6d432ca30d/images/create_workflow.png -------------------------------------------------------------------------------- /images/debug_workflow.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/iflytek/ifly-workflow-mcp-server/8926620b3e8c0c1245cc46acf011dd6d432ca30d/images/debug_workflow.png -------------------------------------------------------------------------------- /images/publish_workflow.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/iflytek/ifly-workflow-mcp-server/8926620b3e8c0c1245cc46acf011dd6d432ca30d/images/publish_workflow.png -------------------------------------------------------------------------------- /poetry.lock: -------------------------------------------------------------------------------- 1 | # This file is automatically @generated by Poetry 2.1.1 and should not be changed by hand. 2 | 3 | [[package]] 4 | name = "annotated-types" 5 | version = "0.7.0" 6 | description = "Reusable constraint types to use with typing.Annotated" 7 | optional = false 8 | python-versions = ">=3.8" 9 | groups = ["main"] 10 | files = [ 11 | {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"}, 12 | {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"}, 13 | ] 14 | 15 | [[package]] 16 | name = "antlr4-python3-runtime" 17 | version = "4.9.3" 18 | description = "ANTLR 4.9.3 runtime for Python 3.7" 19 | optional = false 20 | python-versions = "*" 21 | groups = ["main"] 22 | files = [ 23 | {file = "antlr4-python3-runtime-4.9.3.tar.gz", hash = "sha256:f224469b4168294902bb1efa80a8bf7855f24c99aef99cbefc1bcd3cce77881b"}, 24 | ] 25 | 26 | [[package]] 27 | name = "anyio" 28 | version = "4.9.0" 29 | description = "High level compatibility layer for multiple asynchronous event loop implementations" 30 | optional = false 31 | python-versions = ">=3.9" 32 | groups = ["main"] 33 | files = [ 34 | {file = "anyio-4.9.0-py3-none-any.whl", hash = "sha256:9f76d541cad6e36af7beb62e978876f3b41e3e04f2c1fbf0884604c0a9c4d93c"}, 35 | {file = "anyio-4.9.0.tar.gz", hash = "sha256:673c0c244e15788651a4ff38710fea9675823028a6f08a5eda409e0c9840a028"}, 36 | ] 37 | 38 | [package.dependencies] 39 | idna = ">=2.8" 40 | sniffio = ">=1.1" 41 | typing_extensions = {version = ">=4.5", markers = "python_version < \"3.13\""} 42 | 43 | [package.extras] 44 | doc = ["Sphinx (>=8.2,<9.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx_rtd_theme"] 45 | test = ["anyio[trio]", "blockbuster (>=1.5.23)", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "trustme", "truststore (>=0.9.1) ; 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(>=0.4) ; sys_platform == \"win32\"", "httptools (>=0.6.3)", "python-dotenv (>=0.13)", "pyyaml (>=5.1)", "uvloop (>=0.14.0,!=0.15.0,!=0.15.1) ; sys_platform != \"win32\" and sys_platform != \"cygwin\" and platform_python_implementation != \"PyPy\"", "watchfiles (>=0.13)", "websockets (>=10.4)"] 745 | 746 | [metadata] 747 | lock-version = "2.1" 748 | python-versions = ">=3.11" 749 | content-hash = "ab195446cdce0981d682dcd893e417114fcca02f38ee8ff178ea62c4832a2af1" 750 | -------------------------------------------------------------------------------- /pyproject.toml: -------------------------------------------------------------------------------- 1 | [project] 2 | name = "ifly-workflow-mcp-server" 3 | version = "1.0.0" 4 | description = "This a simple implementation of an MCP server using iFlytek. It enables calling iFlytek workflows through MCP tools." 5 | readme = "README.md" 6 | requires-python = ">=3.11" 7 | dependencies = [ 8 | "httpx==0.28.1", 9 | "mcp==1.5.0", 10 | "pip==25.0.1", 11 | "pytest==8.3.5", 12 | "python-dotenv==1.0.1", 13 | "requests==2.32.3", 14 | "pyyaml==6.0.2" 15 | ] 16 | 17 | [build-system] 18 | requires = ["hatchling", ] 19 | build-backend = "hatchling.build" 20 | 21 | [project.scripts] 22 | ifly_workflow_mcp_server = "mcp_server:main" 23 | 24 | [tool.hatch.build.targets.wheel] 25 | packages = ["src/mcp_server"] 26 | -------------------------------------------------------------------------------- /src/mcp_server/__init__.py: -------------------------------------------------------------------------------- 1 | from . import server 2 | import asyncio 3 | 4 | 5 | def main(): 6 | asyncio.run(server.main()) 7 | 8 | 9 | __all__ = ['main', 'server'] 10 | -------------------------------------------------------------------------------- /src/mcp_server/entities/flow.py: -------------------------------------------------------------------------------- 1 | from typing import Any, Dict 2 | 3 | from pydantic import BaseModel, Field 4 | 5 | 6 | class Flow(BaseModel): 7 | flow_id: str 8 | name: str = '' 9 | description: str = '' 10 | api_key: str 11 | input_schema: Dict[str, Any] = Field(default_factory=dict) 12 | """A JSON Schema object defining the expected parameters for the tool.""" 13 | -------------------------------------------------------------------------------- /src/mcp_server/entities/ifly_client.py: -------------------------------------------------------------------------------- 1 | import json 2 | import os 3 | from abc import ABC 4 | from enum import Enum 5 | from typing import Dict, Any 6 | 7 | import requests 8 | import yaml 9 | 10 | from mcp_server.entities.flow import Flow 11 | 12 | 13 | class SysTool(Enum): 14 | """ 15 | sys tools enum 16 | """ 17 | SYS_UPLOAD_FILE = "SYS_UPLOAD_FILE" 18 | """ Workflow provides file upload """ 19 | 20 | 21 | class IFlyWorkflowClient(ABC): 22 | base_url = "https://xingchen-api.xf-yun.com" 23 | 24 | def __init__(self, config_path: str = os.getenv("CONFIG_PATH")): 25 | """ 26 | init 27 | :param config_path: config path,default is CONFIG_PATH 28 | """ 29 | if not config_path: 30 | raise ValueError("CONFIG_PATH is not set") 31 | 32 | with open(config_path, 'r', encoding='utf-8') as file: 33 | self.flows = [Flow(**flow) for flow in yaml.safe_load(file)] 34 | self.name_idx: Dict[str, int] = {} 35 | 36 | # get flow info 37 | for flow in self.flows: 38 | flow_info = self.get_flow_info(flow.flow_id, flow.api_key) 39 | flow.name = flow.name if flow.name else flow_info["data"]["name"] 40 | flow.description = flow.description if flow.description else flow_info["data"]["description"] 41 | flow.input_schema = flow_info["data"]["inputSchema"] 42 | 43 | self._add_sys_tool() 44 | 45 | # build name_idx 46 | for i, flow in enumerate(self.flows): 47 | self.name_idx[flow.name] = i 48 | 49 | def _add_sys_tool(self): 50 | """ 51 | add default sys tools 52 | :return: 53 | """ 54 | self.flows.append( 55 | # add sys_upload_file 56 | Flow( 57 | flow_id=SysTool.SYS_UPLOAD_FILE.value, 58 | name=SysTool.SYS_UPLOAD_FILE.value, 59 | api_key=self.flows[0].api_key, 60 | description="upload file. Format support: image(jpg、png、bmp、jpeg), doc(pdf)", 61 | input_schema={ 62 | "type": "object", 63 | "properties": { 64 | "file": { 65 | "type": "string", 66 | "description": "file path" 67 | } 68 | }, 69 | "required": ["file"] 70 | } 71 | ) 72 | ) 73 | 74 | def chat_message( 75 | self, 76 | flow: Flow, 77 | inputs: Dict[str, Any], 78 | stream: bool = True 79 | ) -> str: 80 | """ 81 | flow chat request 82 | :param flow: 83 | :param inputs: 84 | :param stream: 85 | :return: 86 | """ 87 | url = f"{self.base_url}/workflow/v1/chat/completions" 88 | headers = { 89 | "Authorization": f"Bearer {flow.api_key}", 90 | "Content-Type": "application/json" 91 | } 92 | data = { 93 | "flow_id": flow.flow_id, 94 | "parameters": inputs, 95 | "stream": stream 96 | } 97 | response = requests.post( 98 | url, headers=headers, json=data, stream=stream) 99 | response.raise_for_status() 100 | if stream: 101 | for line in response.iter_lines(): 102 | if line and line.startswith(b'data:'): 103 | try: 104 | src_content = line[5:].decode('utf-8') 105 | json_data = json.loads(src_content) 106 | if json_data.get("code", 0) != 0: 107 | yield src_content 108 | break 109 | choice = json_data["choices"][0] 110 | yield choice["delta"]["content"] 111 | if choice["finish_reason"] == "stop": 112 | break 113 | except json.JSONDecodeError: 114 | yield f"Error decoding JSON: {line}" 115 | else: 116 | json_data = response.json() 117 | if json_data.get("code", 0) != 0: 118 | yield json.dumps(json_data) 119 | else: 120 | yield json_data["choices"][0]["delta"]["content"] 121 | 122 | def get_flow_info( 123 | self, 124 | flow_id: str, 125 | api_key: str 126 | ) -> Dict[str, Any]: 127 | """ 128 | get flow info, such as flow description, parameters 129 | :param flow_id: 130 | :param api_key: 131 | :return: 132 | """ 133 | url = f"{self.base_url}/workflow/v1/get_flow_info/{flow_id}" 134 | headers = { 135 | "Authorization": f"Bearer {api_key}" 136 | } 137 | response = requests.get(url, headers=headers) 138 | response.raise_for_status() 139 | json_data = response.json() 140 | if json_data.get("code", 0) != 0: 141 | raise ValueError(json_data) 142 | return json_data 143 | 144 | def upload_file( 145 | self, 146 | api_key, 147 | file_path, 148 | ) -> str: 149 | 150 | url = f"{self.base_url}/workflow/v1/upload_file" 151 | headers = { 152 | "Authorization": f"Bearer {api_key}" 153 | } 154 | with open(file_path, "rb") as file: 155 | files = {"file": file} 156 | response = requests.post(url, headers=headers, files=files) 157 | response.raise_for_status() 158 | return response.content.decode('utf-8') 159 | -------------------------------------------------------------------------------- /src/mcp_server/server.py: -------------------------------------------------------------------------------- 1 | import asyncio 2 | from collections.abc import AsyncIterator 3 | from contextlib import asynccontextmanager 4 | from typing import Iterator 5 | 6 | import mcp.server.stdio 7 | import mcp.types as types 8 | from mcp.server import NotificationOptions, Server 9 | from mcp.server.models import InitializationOptions 10 | 11 | from mcp_server.entities.ifly_client import IFlyWorkflowClient, SysTool 12 | 13 | 14 | @asynccontextmanager 15 | async def server_lifespan(server: Server) -> AsyncIterator[dict]: 16 | """Manage server startup and shutdown lifecycle.""" 17 | # Initialize resources on startup 18 | yield {"ifly_client": IFlyWorkflowClient()} 19 | 20 | 21 | server = Server("ifly_workflow_mcp_server", lifespan=server_lifespan) 22 | 23 | 24 | @server.list_tools() 25 | async def handle_list_tools() -> list[types.Tool]: 26 | """ 27 | List available tools,and convert them to MCP client can call. 28 | :return: 29 | """ 30 | tools = [] 31 | ctx = server.request_context 32 | for i, flow in enumerate(ctx.lifespan_context["ifly_client"].flows): 33 | tools.append( 34 | types.Tool( 35 | name=flow.name, 36 | description=flow.description, 37 | inputSchema=flow.input_schema, 38 | ) 39 | ) 40 | return tools 41 | 42 | 43 | @server.call_tool() 44 | async def handle_call_tool( 45 | name: str, arguments: dict | None 46 | ) -> list[types.TextContent | types.ImageContent | types.EmbeddedResource]: 47 | """ 48 | Process valid tool call requests and convert them to MCP responses 49 | :param name: tool name 50 | :param arguments: tool arguments 51 | :return: 52 | """ 53 | ifly_client = server.request_context.lifespan_context["ifly_client"] 54 | if name not in ifly_client.name_idx: 55 | raise ValueError(f"Invalid tool name: {name}") 56 | flow = ifly_client.flows[ifly_client.name_idx[name]] 57 | if name == SysTool.SYS_UPLOAD_FILE.value: 58 | data = ifly_client.upload_file( 59 | flow.api_key, 60 | arguments["file"], 61 | ) 62 | else: 63 | data = ifly_client.chat_message( 64 | flow, 65 | arguments, 66 | ) 67 | mcp_out = [] 68 | 69 | if isinstance(data, Iterator): 70 | for res in data: 71 | mcp_out.append( 72 | types.TextContent( 73 | type='text', 74 | text=res 75 | ) 76 | ) 77 | else: 78 | mcp_out.append( 79 | types.TextContent( 80 | type='text', 81 | text=data 82 | ) 83 | ) 84 | return mcp_out 85 | 86 | 87 | async def main(): 88 | # Run the server using stdin/stdout streams 89 | async with mcp.server.stdio.stdio_server() as (read_stream, write_stream): 90 | await server.run( 91 | read_stream, 92 | write_stream, 93 | InitializationOptions( 94 | server_name="ifly_workflow_mcp_server", 95 | server_version="0.0.1", 96 | capabilities=server.get_capabilities( 97 | notification_options=NotificationOptions(), 98 | experimental_capabilities={}, 99 | ), 100 | ), 101 | ) 102 | 103 | 104 | if __name__ == "__main__": 105 | asyncio.run(main()) 106 | -------------------------------------------------------------------------------- /src/test/__init__.py: -------------------------------------------------------------------------------- 1 | import os 2 | 3 | os.environ["CONFIG_PATH"] = "../../config.yaml" -------------------------------------------------------------------------------- /src/test/pytest.ini: -------------------------------------------------------------------------------- 1 | [pytest] 2 | log_cli = true 3 | log_cli_level = info -------------------------------------------------------------------------------- /src/test/test_ifly_api.py: -------------------------------------------------------------------------------- 1 | import logging 2 | 3 | from typing import Iterator 4 | 5 | 6 | def test_chat(): 7 | from mcp_server.entities.ifly_client import IFlyWorkflowClient 8 | ifly_client = IFlyWorkflowClient() 9 | resp = ifly_client.chat_message( 10 | ifly_client.flows[0], 11 | { 12 | "AGENT_USER_INPUT": "a picture of a cat" 13 | } 14 | ) 15 | if isinstance(resp, Iterator): 16 | for res in resp: 17 | logging.info(res) 18 | else: 19 | logging.info(resp) 20 | -------------------------------------------------------------------------------- /src/test/test_server.py: -------------------------------------------------------------------------------- 1 | import logging 2 | 3 | from mcp import ClientSession, StdioServerParameters, types 4 | from mcp.client.stdio import stdio_client 5 | 6 | from mcp_server.entities.ifly_client import SysTool 7 | 8 | # Create server parameters for stdio connection 9 | server_params = StdioServerParameters( 10 | command="uvx", # Executable 11 | args=[ 12 | "--from", 13 | "../..", 14 | "ifly_workflow_mcp_server" 15 | ], # Optional command line arguments 16 | env={ 17 | "CONFIG_PATH": "../../config.yaml" 18 | }, # Optional environment variables 19 | ) 20 | 21 | 22 | # Optional: create a sampling callback 23 | async def handle_sampling_message( 24 | message: types.CreateMessageRequestParams, 25 | ) -> types.CreateMessageResult: 26 | return types.CreateMessageResult( 27 | role="assistant", 28 | content=types.TextContent( 29 | type="text", 30 | text="Hello, world! from model", 31 | ), 32 | model="gpt-3.5-turbo", 33 | stopReason="endTurn", 34 | ) 35 | 36 | 37 | async def run(): 38 | async with stdio_client(server_params) as (read, write): 39 | async with ClientSession( 40 | read, write, sampling_callback=handle_sampling_message 41 | ) as session: 42 | # Initialize the connection 43 | await session.initialize() 44 | 45 | # List available tools 46 | tools = await session.list_tools() 47 | logging.info(f"tools: {tools}") 48 | 49 | # Call a tool 50 | sys_upload_file_result = await session.call_tool( 51 | SysTool.SYS_UPLOAD_FILE.value, 52 | arguments={"file": "/Users/hygao1024/Documents/iFlytek/Work/测试图片.jpg"} 53 | ) 54 | logging.info(f"call sys_upload_file result: {sys_upload_file_result}") 55 | 56 | image_generator_result = await session.call_tool("image_generator", arguments={"AGENT_USER_INPUT": "你好"}) 57 | logging.info(f"call image_generator result: {image_generator_result}") 58 | 59 | llm_test_result = await session.call_tool("llm_test", arguments={"AGENT_USER_INPUT": "你好"}) 60 | logging.info(f"call llm_test_result result: {llm_test_result}") 61 | 62 | 63 | def test_run(): 64 | import asyncio 65 | 66 | 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