├── .python-version ├── flux_kontext_mcp ├── __main__.py ├── __init__.py └── server.py ├── README.md ├── pyproject.toml ├── LICENSE ├── .github └── workflows │ └── publish.yml ├── .gitignore └── uv.lock /.python-version: -------------------------------------------------------------------------------- 1 | 3.12 2 | -------------------------------------------------------------------------------- /flux_kontext_mcp/__main__.py: -------------------------------------------------------------------------------- 1 | from flux_kontext_mcp import main 2 | 3 | main() -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Flux.1 Kontext MCP Server 2 | 3 | MCP server configuration: 4 | 5 | ```json 6 | { 7 | "mcpServers": { 8 | "flux_kontext_mcp": { 9 | "command": "uvx", 10 | "args": ["flux-kontext-mcp"], 11 | "env": { 12 | "REPLICATE_API_TOKEN": "your_replicate_api_token" 13 | } 14 | } 15 | } 16 | } 17 | ``` 18 | 19 | ## MCP tools 20 | 21 | - flux_kontext_generate 22 | - flux_kontext_async_generate 23 | - flux_kontext_get_prediction 24 | - flux_kontext_list_predictions 25 | - flux_kontext_cancel_prediction 26 | - flux_kontext_wait_for_prediction 27 | - flux_kontext_get_model_info 28 | 29 | 30 | 31 | -------------------------------------------------------------------------------- /flux_kontext_mcp/__init__.py: -------------------------------------------------------------------------------- 1 | """flux_kontext_mcp package""" 2 | 3 | import argparse 4 | from .server import mcp 5 | 6 | def main(): 7 | """Entry point for the MCP server""" 8 | # Parse command line arguments 9 | parser = argparse.ArgumentParser(description="Flux Kontext MCP Server") 10 | parser.add_argument('transport', nargs='?', default='stdio', choices=['stdio', 'sse', 'streamable-http'], 11 | help='Transport type (stdio, sse, or streamable-http)') 12 | args = parser.parse_args() 13 | 14 | # Run the MCP server with the specified transport 15 | mcp.run(transport=args.transport) 16 | 17 | if __name__ == "__main__": 18 | main() 19 | -------------------------------------------------------------------------------- /pyproject.toml: -------------------------------------------------------------------------------- 1 | [build-system] 2 | requires = ["hatchling"] 3 | build-backend = "hatchling.build" 4 | 5 | [project] 6 | name = "flux-kontext-mcp" 7 | version = "0.0.4" 8 | description = "Flux.1 Kontext MCP Server" 9 | readme = "README.md" 10 | requires-python = ">=3.10" 11 | classifiers = [ 12 | "Programming Language :: Python :: 3", 13 | "License :: OSI Approved :: MIT License", 14 | "Operating System :: OS Independent", 15 | ] 16 | dependencies = [ 17 | "mcp==1.8.1", 18 | "openai>=1.86.0", 19 | "replicate>=1.0.7", 20 | "requests>=2.32.3", 21 | ] 22 | 23 | [project.scripts] 24 | flux-kontext-mcp = "flux_kontext_mcp:main" 25 | 26 | [project.urls] 27 | "Homepage" = "https://github.com/sugarforever/flux-kontext-mcp" 28 | "Bug Tracker" = "https://github.com/sugarforever/flux-kontext-mcp/issues" 29 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2025 sugarforever 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 | -------------------------------------------------------------------------------- /.github/workflows/publish.yml: -------------------------------------------------------------------------------- 1 | name: Publish to PyPI 2 | 3 | on: 4 | push: 5 | branches: 6 | - main 7 | release: 8 | types: [created] 9 | 10 | jobs: 11 | deploy: 12 | runs-on: ubuntu-latest 13 | # Only publish to PyPI on release 14 | if: github.event_name == 'release' 15 | steps: 16 | - uses: actions/checkout@v4 17 | - name: Set up Python 18 | uses: actions/setup-python@v4 19 | with: 20 | python-version: '3.x' 21 | - name: Install dependencies 22 | run: | 23 | python -m pip install --upgrade pip 24 | pip install build twine 25 | - name: Build package 26 | run: python -m build 27 | - name: Publish package 28 | env: 29 | TWINE_USERNAME: __token__ 30 | TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }} 31 | run: | 32 | twine upload dist/* 33 | 34 | test: 35 | runs-on: ubuntu-latest 36 | # Run tests on every push to main 37 | if: github.event_name == 'push' 38 | steps: 39 | - uses: actions/checkout@v4 40 | - name: Set up Python 41 | uses: actions/setup-python@v4 42 | with: 43 | python-version: '3.x' 44 | - name: Install dependencies 45 | run: | 46 | python -m pip install --upgrade pip 47 | pip install build 48 | - name: Build package 49 | run: python -m build 50 | - name: Test build 51 | env: 52 | REPLICATE_API_TOKEN: mock_key_for_testing 53 | run: | 54 | python -m pip install dist/*.whl 55 | python -c "import flux_kontext_mcp" -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | share/python-wheels/ 24 | *.egg-info/ 25 | .installed.cfg 26 | *.egg 27 | MANIFEST 28 | 29 | # PyInstaller 30 | # Usually these files are written by a python script from a template 31 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 32 | *.manifest 33 | *.spec 34 | 35 | # Installer logs 36 | pip-log.txt 37 | pip-delete-this-directory.txt 38 | 39 | # Unit test / coverage reports 40 | htmlcov/ 41 | .tox/ 42 | .nox/ 43 | .coverage 44 | .coverage.* 45 | .cache 46 | nosetests.xml 47 | coverage.xml 48 | *.cover 49 | *.py,cover 50 | .hypothesis/ 51 | .pytest_cache/ 52 | cover/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | db.sqlite3-journal 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | .pybuilder/ 76 | target/ 77 | 78 | # Jupyter Notebook 79 | .ipynb_checkpoints 80 | 81 | # IPython 82 | profile_default/ 83 | ipython_config.py 84 | 85 | # pyenv 86 | # For a library or package, you might want to ignore these files since the code is 87 | # intended to run in multiple environments; otherwise, check them in: 88 | # .python-version 89 | 90 | # pipenv 91 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 92 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 93 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 94 | # install all needed dependencies. 95 | #Pipfile.lock 96 | 97 | # UV 98 | # Similar to Pipfile.lock, it is generally recommended to include uv.lock in version control. 99 | # This is especially recommended for binary packages to ensure reproducibility, and is more 100 | # commonly ignored for libraries. 101 | #uv.lock 102 | 103 | # poetry 104 | # Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. 105 | # This is especially recommended for binary packages to ensure reproducibility, and is more 106 | # commonly ignored for libraries. 107 | # https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control 108 | #poetry.lock 109 | 110 | # pdm 111 | # Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. 112 | #pdm.lock 113 | # pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it 114 | # in version control. 115 | # https://pdm.fming.dev/latest/usage/project/#working-with-version-control 116 | .pdm.toml 117 | .pdm-python 118 | .pdm-build/ 119 | 120 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm 121 | __pypackages__/ 122 | 123 | # Celery stuff 124 | celerybeat-schedule 125 | celerybeat.pid 126 | 127 | # SageMath parsed files 128 | *.sage.py 129 | 130 | # Environments 131 | .env 132 | .venv 133 | env/ 134 | venv/ 135 | ENV/ 136 | env.bak/ 137 | venv.bak/ 138 | 139 | # Spyder project settings 140 | .spyderproject 141 | .spyproject 142 | 143 | # Rope project settings 144 | .ropeproject 145 | 146 | # mkdocs documentation 147 | /site 148 | 149 | # mypy 150 | .mypy_cache/ 151 | .dmypy.json 152 | dmypy.json 153 | 154 | # Pyre type checker 155 | .pyre/ 156 | 157 | # pytype static type analyzer 158 | .pytype/ 159 | 160 | # Cython debug symbols 161 | cython_debug/ 162 | 163 | # PyCharm 164 | # JetBrains specific template is maintained in a separate JetBrains.gitignore that can 165 | # be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore 166 | # and can be added to the global gitignore or merged into this file. For a more nuclear 167 | # option (not recommended) you can uncomment the following to ignore the entire idea folder. 168 | #.idea/ 169 | 170 | # Abstra 171 | # Abstra is an AI-powered process automation framework. 172 | # Ignore directories containing user credentials, local state, and settings. 173 | # Learn more at https://abstra.io/docs 174 | .abstra/ 175 | 176 | # Visual Studio Code 177 | # Visual Studio Code specific template is maintained in a separate VisualStudioCode.gitignore 178 | # that can be found at https://github.com/github/gitignore/blob/main/Global/VisualStudioCode.gitignore 179 | # and can be added to the global gitignore or merged into this file. However, if you prefer, 180 | # you could uncomment the following to ignore the enitre vscode folder 181 | # .vscode/ 182 | 183 | # Ruff stuff: 184 | .ruff_cache/ 185 | 186 | # PyPI configuration file 187 | .pypirc 188 | 189 | # Cursor 190 | # Cursor is an AI-powered code editor. `.cursorignore` specifies files/directories to 191 | # exclude from AI features like autocomplete and code analysis. Recommended for sensitive data 192 | # refer to https://docs.cursor.com/context/ignore-files 193 | .cursorignore 194 | .cursorindexingignore -------------------------------------------------------------------------------- /flux_kontext_mcp/server.py: -------------------------------------------------------------------------------- 1 | import os 2 | import sys 3 | import argparse 4 | import logging 5 | import time 6 | from typing import Any, Dict, List, Optional 7 | import replicate 8 | from mcp.server.fastmcp import FastMCP 9 | from openai import OpenAI 10 | 11 | # Configure logging 12 | logging.basicConfig( 13 | level=logging.INFO, 14 | format='%(asctime)s - %(name)s - %(levelname)s - %(message)s', 15 | handlers=[ 16 | logging.FileHandler('flux_kontext_mcp.log') 17 | ] 18 | ) 19 | logger = logging.getLogger(__name__) 20 | 21 | def get_api_token() -> str: 22 | """Get the Replicate API token from environment variables""" 23 | logger.info("Retrieving Replicate API token from environment") 24 | api_token = os.getenv("REPLICATE_API_TOKEN") 25 | if not api_token: 26 | logger.error("REPLICATE_API_TOKEN environment variable not found") 27 | raise ValueError("REPLICATE_API_TOKEN environment variable is required") 28 | logger.info("Replicate API token successfully retrieved") 29 | return api_token 30 | 31 | # Set the API token for replicate 32 | try: 33 | os.environ["REPLICATE_API_TOKEN"] = get_api_token() 34 | logger.info("Replicate API token set successfully") 35 | except Exception as e: 36 | logger.error(f"Failed to set Replicate API token: {str(e)}") 37 | raise 38 | 39 | mcp = FastMCP("flux-kontext-pro") 40 | logger.info("FastMCP server initialized with name: flux-kontext-pro") 41 | 42 | def rewrite_kontext_prompt(prompt: str) -> str: 43 | """ 44 | Rewrite the prompt to be more specific and detailed using OpenAI API. 45 | Falls back to original prompt if API is unavailable or fails. 46 | """ 47 | logger.info(f"Starting prompt rewrite for prompt: {prompt[:100]}...") 48 | 49 | api_key = os.getenv("OPENAI_API_KEY") 50 | if not api_key: 51 | logger.warning("OPENAI_API_KEY not found, using original prompt") 52 | return prompt 53 | 54 | try: 55 | # Get OpenAI configuration from environment variables 56 | base_url = os.getenv("OPENAI_BASE_URL", "https://api.openai.com/v1") 57 | model_name = os.getenv("OPENAI_MODEL_NAME", "gpt-4o") 58 | 59 | logger.info(f"Using OpenAI API with base_url: {base_url}, model: {model_name}") 60 | 61 | # Initialize OpenAI client 62 | client = OpenAI( 63 | api_key=api_key, 64 | base_url=base_url 65 | ) 66 | logger.debug("OpenAI client initialized successfully") 67 | 68 | # System prompt to instruct the model 69 | system_prompt = """You are a helpful assistant that translates and polishes prompts for image editing, to English. Your task is to: 70 | 71 | 1. If the input prompt is not in English, translate it to English 72 | 2. Keep the original intention and meaning intact 73 | 3. Do not add creative elements that weren't in the original prompt 74 | 4. Return only the improved prompt, no explanations or additional text 75 | 76 | Be conservative and faithful to the original intent.""" 77 | 78 | logger.info("Making OpenAI API call for prompt rewriting") 79 | start_time = time.time() 80 | 81 | # Make the API call with temperature 0 for conservative output 82 | response = client.chat.completions.create( 83 | model=model_name, 84 | messages=[ 85 | {"role": "system", "content": system_prompt}, 86 | {"role": "user", "content": prompt} 87 | ], 88 | temperature=0, 89 | max_tokens=500 90 | ) 91 | 92 | api_duration = time.time() - start_time 93 | logger.info(f"OpenAI API call completed in {api_duration:.2f} seconds") 94 | logger.info(f"OpenAI API response: {response}") 95 | # Extract the improved prompt 96 | improved_prompt = response.choices[0].message.content.strip() 97 | 98 | if improved_prompt: 99 | logger.info(f"Prompt successfully rewritten: {improved_prompt[:100]}...") 100 | return improved_prompt 101 | else: 102 | logger.warning("OpenAI API returned empty response, using original prompt") 103 | return prompt 104 | 105 | except Exception as e: 106 | # Return original prompt if any error occurs 107 | logger.error(f"OpenAI API call failed: {str(e)}, falling back to original prompt") 108 | return prompt 109 | 110 | @mcp.tool() 111 | def flux_kontext_generate( 112 | prompt: str, 113 | input_image: str, 114 | aspect_ratio: str = "match_input_image", 115 | output_format: str = "png", 116 | safety_tolerance: int = 2 117 | ) -> Dict[str, Any]: 118 | """ 119 | Generate images using Flux Kontext Pro model from Replicate. 120 | 121 | Args: 122 | prompt (str): Text prompt describing the desired image or modifications 123 | input_image (str): URL of the input image to modify. If not provided, generates from scratch 124 | aspect_ratio (str): Aspect ratio for the output image. Options: "match_input_image", "1:1", "16:9", "9:16", "4:3", "3:4", "3:2", "2:3" 125 | output_format (str): Output image format. Options: "png", "jpg", "webp" 126 | safety_tolerance (int): Safety tolerance level (0-5). Higher values are more permissive 127 | 128 | Returns: 129 | Dict[str, Any]: Generated image URL and metadata or error information 130 | """ 131 | logger.info(f"Starting flux_kontext_generate with prompt: {prompt[:100]}...") 132 | logger.info(f"Parameters - aspect_ratio: {aspect_ratio}, output_format: {output_format}, safety_tolerance: {safety_tolerance}") 133 | logger.info(f"Input image provided: {bool(input_image)}") 134 | 135 | try: 136 | # Rewrite the prompt for better results 137 | rewritten_prompt = rewrite_kontext_prompt(prompt) 138 | 139 | # Prepare the input parameters 140 | input_params = { 141 | "prompt": rewritten_prompt, 142 | "aspect_ratio": aspect_ratio, 143 | "output_format": output_format, 144 | "safety_tolerance": safety_tolerance 145 | } 146 | 147 | # Add input image if provided 148 | if input_image: 149 | input_params["input_image"] = input_image 150 | logger.info(f"Added input image to parameters: {input_image[:100]}...") 151 | 152 | logger.info("Starting Replicate model execution") 153 | start_time = time.time() 154 | 155 | # Run the model 156 | output = replicate.run( 157 | "black-forest-labs/flux-kontext-pro", 158 | input=input_params 159 | ) 160 | 161 | execution_duration = time.time() - start_time 162 | logger.info(f"Replicate model execution completed in {execution_duration:.2f} seconds") 163 | logger.info(f"Generated image URL: {output}") 164 | 165 | result = { 166 | "status": "success", 167 | "image_url": output, 168 | "model": "black-forest-labs/flux-kontext-pro", 169 | "input": input_params, 170 | "execution_time": execution_duration 171 | } 172 | 173 | logger.info("flux_kontext_generate completed successfully") 174 | return result 175 | 176 | except Exception as e: 177 | logger.error(f"flux_kontext_generate failed: {str(e)}") 178 | return {"error": f"Image generation failed: {str(e)}"} 179 | 180 | @mcp.tool() 181 | def flux_kontext_async_generate( 182 | prompt: str, 183 | input_image: str, 184 | aspect_ratio: str = "match_input_image", 185 | output_format: str = "png", 186 | safety_tolerance: int = 2 187 | ) -> Dict[str, Any]: 188 | """ 189 | Start an asynchronous image generation job using Flux Kontext Pro model. 190 | Use this for non-blocking requests when you don't need to wait for completion. 191 | 192 | Args: 193 | prompt (str): Text prompt describing the desired image or modifications 194 | input_image (Optional[str]): URL of the input image to modify 195 | aspect_ratio (str): Aspect ratio for the output image 196 | output_format (str): Output image format 197 | safety_tolerance (int): Safety tolerance level (0-5) 198 | 199 | Returns: 200 | Dict[str, Any]: Prediction object with ID and initial status 201 | """ 202 | logger.info(f"Starting flux_kontext_async_generate with prompt: {prompt[:100]}...") 203 | logger.info(f"Parameters - aspect_ratio: {aspect_ratio}, output_format: {output_format}, safety_tolerance: {safety_tolerance}") 204 | logger.info(f"Input image provided: {bool(input_image)}") 205 | 206 | try: 207 | # Rewrite the prompt for better results 208 | rewritten_prompt = rewrite_kontext_prompt(prompt) 209 | 210 | # Prepare the input parameters 211 | input_params = { 212 | "prompt": rewritten_prompt, 213 | "aspect_ratio": aspect_ratio, 214 | "output_format": output_format, 215 | "safety_tolerance": safety_tolerance 216 | } 217 | 218 | # Add input image if provided 219 | if input_image: 220 | input_params["input_image"] = input_image 221 | logger.info(f"Added input image to parameters: {input_image[:100]}...") 222 | 223 | logger.info("Creating async prediction on Replicate") 224 | 225 | # Create a prediction without waiting 226 | prediction = replicate.predictions.create( 227 | model="black-forest-labs/flux-kontext-pro", 228 | input=input_params 229 | ) 230 | 231 | logger.info(f"Async prediction created with ID: {prediction.id}") 232 | logger.info(f"Initial status: {prediction.status}") 233 | 234 | result = { 235 | "prediction_id": prediction.id, 236 | "status": prediction.status, 237 | "created_at": prediction.created_at.isoformat() if prediction.created_at else None, 238 | "input": input_params, 239 | "urls": { 240 | "get": prediction.urls.get if hasattr(prediction, 'urls') else None, 241 | "cancel": prediction.urls.cancel if hasattr(prediction, 'urls') else None 242 | } 243 | } 244 | 245 | logger.info("flux_kontext_async_generate completed successfully") 246 | return result 247 | 248 | except Exception as e: 249 | logger.error(f"flux_kontext_async_generate failed: {str(e)}") 250 | return {"error": f"Async generation failed: {str(e)}"} 251 | 252 | @mcp.tool() 253 | def flux_kontext_get_prediction(prediction_id: str) -> Dict[str, Any]: 254 | """ 255 | Get the status and result of a specific prediction by ID. 256 | 257 | Args: 258 | prediction_id (str): The ID of the prediction to check 259 | 260 | Returns: 261 | Dict[str, Any]: Prediction status, result, and metadata 262 | """ 263 | logger.info(f"Getting prediction status for ID: {prediction_id}") 264 | 265 | try: 266 | prediction = replicate.predictions.get(prediction_id) 267 | 268 | logger.info(f"Prediction {prediction_id} status: {prediction.status}") 269 | 270 | if prediction.status == "succeeded": 271 | logger.info(f"Prediction {prediction_id} completed successfully") 272 | elif prediction.status == "failed": 273 | logger.error(f"Prediction {prediction_id} failed: {prediction.error}") 274 | elif prediction.status == "canceled": 275 | logger.info(f"Prediction {prediction_id} was canceled") 276 | 277 | result = { 278 | "id": prediction.id, 279 | "status": prediction.status, 280 | "created_at": prediction.created_at.isoformat() if prediction.created_at else None, 281 | "started_at": prediction.started_at.isoformat() if prediction.started_at else None, 282 | "completed_at": prediction.completed_at.isoformat() if prediction.completed_at else None, 283 | "output": prediction.output, 284 | "error": prediction.error, 285 | "input": prediction.input, 286 | "model": prediction.model, 287 | "logs": prediction.logs 288 | } 289 | 290 | logger.info("flux_kontext_get_prediction completed successfully") 291 | return result 292 | 293 | except Exception as e: 294 | logger.error(f"flux_kontext_get_prediction failed: {str(e)}") 295 | return {"error": f"Failed to get prediction: {str(e)}"} 296 | 297 | @mcp.tool() 298 | def flux_kontext_list_predictions(limit: int = 20) -> Dict[str, Any]: 299 | """ 300 | List recent predictions for your account. 301 | 302 | Args: 303 | limit (int): Maximum number of predictions to return (default: 20) 304 | 305 | Returns: 306 | Dict[str, Any]: List of recent predictions with their status and metadata 307 | """ 308 | logger.info(f"Listing predictions with limit: {limit}") 309 | 310 | try: 311 | # Get predictions with limit 312 | logger.info("Fetching predictions from Replicate") 313 | predictions_list = list(replicate.predictions.list())[:limit] 314 | logger.info(f"Retrieved {len(predictions_list)} total predictions") 315 | 316 | # Filter for Flux Kontext Pro predictions 317 | flux_predictions = [] 318 | for pred in predictions_list: 319 | if pred.model and "flux-kontext-pro" in pred.model: 320 | flux_predictions.append({ 321 | "id": pred.id, 322 | "status": pred.status, 323 | "created_at": pred.created_at.isoformat() if pred.created_at else None, 324 | "completed_at": pred.completed_at.isoformat() if pred.completed_at else None, 325 | "model": pred.model, 326 | "input_prompt": pred.input.get("prompt") if pred.input else None, 327 | "has_output": pred.output is not None 328 | }) 329 | 330 | logger.info(f"Found {len(flux_predictions)} Flux Kontext Pro predictions") 331 | 332 | result = { 333 | "predictions": flux_predictions, 334 | "total_returned": len(flux_predictions) 335 | } 336 | 337 | logger.info("flux_kontext_list_predictions completed successfully") 338 | return result 339 | 340 | except Exception as e: 341 | logger.error(f"flux_kontext_list_predictions failed: {str(e)}") 342 | return {"error": f"Failed to list predictions: {str(e)}"} 343 | 344 | @mcp.tool() 345 | def flux_kontext_cancel_prediction(prediction_id: str) -> Dict[str, Any]: 346 | """ 347 | Cancel a running prediction. 348 | 349 | Args: 350 | prediction_id (str): The ID of the prediction to cancel 351 | 352 | Returns: 353 | Dict[str, Any]: Cancellation status and updated prediction info 354 | """ 355 | logger.info(f"Canceling prediction with ID: {prediction_id}") 356 | 357 | try: 358 | prediction = replicate.predictions.cancel(prediction_id) 359 | 360 | logger.info(f"Prediction {prediction_id} cancellation requested") 361 | logger.info(f"New status: {prediction.status}") 362 | 363 | result = { 364 | "id": prediction.id, 365 | "status": prediction.status, 366 | "created_at": prediction.created_at.isoformat() if prediction.created_at else None, 367 | "completed_at": prediction.completed_at.isoformat() if prediction.completed_at else None, 368 | "error": prediction.error, 369 | "cancelled": prediction.status == "canceled" 370 | } 371 | 372 | if result["cancelled"]: 373 | logger.info(f"Prediction {prediction_id} successfully canceled") 374 | else: 375 | logger.warning(f"Prediction {prediction_id} cancellation may not have succeeded, status: {prediction.status}") 376 | 377 | logger.info("flux_kontext_cancel_prediction completed successfully") 378 | return result 379 | 380 | except Exception as e: 381 | logger.error(f"flux_kontext_cancel_prediction failed: {str(e)}") 382 | return {"error": f"Failed to cancel prediction: {str(e)}"} 383 | 384 | @mcp.tool() 385 | def flux_kontext_wait_for_prediction(prediction_id: str, timeout: int = 300) -> Dict[str, Any]: 386 | """ 387 | Wait for a prediction to complete with optional timeout. 388 | 389 | Args: 390 | prediction_id (str): The ID of the prediction to wait for 391 | timeout (int): Maximum time to wait in seconds (default: 300) 392 | 393 | Returns: 394 | Dict[str, Any]: Final prediction result or timeout error 395 | """ 396 | logger.info(f"Waiting for prediction {prediction_id} with timeout: {timeout} seconds") 397 | 398 | try: 399 | start_time = time.time() 400 | check_count = 0 401 | 402 | while time.time() - start_time < timeout: 403 | check_count += 1 404 | prediction = replicate.predictions.get(prediction_id) 405 | 406 | elapsed_time = int(time.time() - start_time) 407 | logger.info(f"Check #{check_count} - Prediction {prediction_id} status: {prediction.status} (elapsed: {elapsed_time}s)") 408 | 409 | if prediction.status in ["succeeded", "failed", "canceled"]: 410 | logger.info(f"Prediction {prediction_id} reached final status: {prediction.status}") 411 | 412 | result = { 413 | "id": prediction.id, 414 | "status": prediction.status, 415 | "created_at": prediction.created_at.isoformat() if prediction.created_at else None, 416 | "completed_at": prediction.completed_at.isoformat() if prediction.completed_at else None, 417 | "output": prediction.output, 418 | "error": prediction.error, 419 | "waited_seconds": elapsed_time, 420 | "checks_performed": check_count 421 | } 422 | 423 | if prediction.status == "succeeded": 424 | logger.info(f"Prediction {prediction_id} completed successfully after {elapsed_time} seconds") 425 | elif prediction.status == "failed": 426 | logger.error(f"Prediction {prediction_id} failed after {elapsed_time} seconds: {prediction.error}") 427 | else: 428 | logger.info(f"Prediction {prediction_id} was canceled after {elapsed_time} seconds") 429 | 430 | return result 431 | 432 | time.sleep(2) # Check every 2 seconds 433 | 434 | logger.warning(f"Prediction {prediction_id} timed out after {timeout} seconds") 435 | return {"error": f"Prediction timed out after {timeout} seconds", "status": "timeout"} 436 | 437 | except Exception as e: 438 | logger.error(f"flux_kontext_wait_for_prediction failed: {str(e)}") 439 | return {"error": f"Failed to wait for prediction: {str(e)}"} 440 | 441 | @mcp.tool() 442 | def flux_kontext_get_model_info(random_string: str = "dummy") -> Dict[str, Any]: 443 | """ 444 | Get information about the Flux Kontext Pro model. 445 | 446 | Returns: 447 | Dict[str, Any]: Model information including description, input schema, etc. 448 | """ 449 | logger.info("Getting Flux Kontext Pro model information") 450 | 451 | try: 452 | model = replicate.models.get("black-forest-labs/flux-kontext-pro") 453 | 454 | logger.info("Successfully retrieved model information") 455 | 456 | result = { 457 | "name": model.name, 458 | "description": model.description, 459 | "visibility": model.visibility, 460 | "github_url": model.github_url, 461 | "paper_url": model.paper_url, 462 | "license_url": model.license_url, 463 | "cover_image_url": model.cover_image_url, 464 | "latest_version": { 465 | "id": model.latest_version.id if model.latest_version else None, 466 | "created_at": model.latest_version.created_at.isoformat() if model.latest_version and model.latest_version.created_at else None 467 | } 468 | } 469 | 470 | logger.info("flux_kontext_get_model_info completed successfully") 471 | return result 472 | 473 | except Exception as e: 474 | logger.error(f"flux_kontext_get_model_info failed: {str(e)}") 475 | return {"error": f"Failed to get model info: {str(e)}"} 476 | 477 | if __name__ == "__main__": 478 | logger.info("Starting Flux Kontext Pro MCP Server") 479 | 480 | # Parse command line arguments 481 | parser = argparse.ArgumentParser(description="Flux Kontext Pro MCP Server") 482 | parser.add_argument('transport', nargs='?', default='stdio', choices=['stdio', 'sse', 'streamable-http'], 483 | help='Transport type (stdio, sse, or streamable-http)') 484 | args = parser.parse_args() 485 | 486 | logger.info(f"Server configuration - Transport: {args.transport}") 487 | 488 | # Log environment variables status (without exposing sensitive data) 489 | logger.info(f"Environment check - REPLICATE_API_TOKEN: {'SET' if os.getenv('REPLICATE_API_TOKEN') else 'NOT SET'}") 490 | logger.info(f"Environment check - OPENAI_API_KEY: {'SET' if os.getenv('OPENAI_API_KEY') else 'NOT SET'}") 491 | 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