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# Directory Structure

```
├── .env.example
├── .gitignore
├── Dockerfile
├── LICENSE
├── mcp_server_deepseek
│   ├── config.py
│   └── server.py
├── README.md
└── requirements.txt
```

# Files

--------------------------------------------------------------------------------
/.env.example:
--------------------------------------------------------------------------------

```
DEEPSEEK_API_KEY=your_api_key_here
```

--------------------------------------------------------------------------------
/.gitignore:
--------------------------------------------------------------------------------

```
# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class

# C extensions
*.so

# Distribution / packaging
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
share/python-wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST

# PyInstaller
#  Usually these files are written by a python script from a template
#  before PyInstaller builds the exe, so as to inject date/other infos into it.
*.manifest
*.spec

# Installer logs
pip-log.txt
pip-delete-this-directory.txt

# Unit test / coverage reports
htmlcov/
.tox/
.nox/
.coverage
.coverage.*
.cache
nosetests.xml
coverage.xml
*.cover
*.py,cover
.hypothesis/
.pytest_cache/
cover/

# Translations
*.mo
*.pot

# Django stuff:
*.log
local_settings.py
db.sqlite3
db.sqlite3-journal

# Flask stuff:
instance/
.webassets-cache

# Scrapy stuff:
.scrapy

# Sphinx documentation
docs/_build/

# PyBuilder
.pybuilder/
target/

# Jupyter Notebook
.ipynb_checkpoints

# IPython
profile_default/
ipython_config.py

# pyenv
#   For a library or package, you might want to ignore these files since the code is
#   intended to run in multiple environments; otherwise, check them in:
# .python-version

# pipenv
#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
#   However, in case of collaboration, if having platform-specific dependencies or dependencies
#   having no cross-platform support, pipenv may install dependencies that don't work, or not
#   install all needed dependencies.
#Pipfile.lock

# UV
#   Similar to Pipfile.lock, it is generally recommended to include uv.lock in version control.
#   This is especially recommended for binary packages to ensure reproducibility, and is more
#   commonly ignored for libraries.
#uv.lock

# poetry
#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
#   This is especially recommended for binary packages to ensure reproducibility, and is more
#   commonly ignored for libraries.
#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
#poetry.lock

# pdm
#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
#pdm.lock
#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
#   in version control.
#   https://pdm.fming.dev/latest/usage/project/#working-with-version-control
.pdm.toml
.pdm-python
.pdm-build/

# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
__pypackages__/

# Celery stuff
celerybeat-schedule
celerybeat.pid

# SageMath parsed files
*.sage.py

# Environments
.env
.venv
env/
venv/
ENV/
env.bak/
venv.bak/

# Spyder project settings
.spyderproject
.spyproject

# Rope project settings
.ropeproject

# mkdocs documentation
/site

# mypy
.mypy_cache/
.dmypy.json
dmypy.json

# Pyre type checker
.pyre/

# pytype static type analyzer
.pytype/

# Cython debug symbols
cython_debug/

# PyCharm
#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
#  and can be added to the global gitignore or merged into this file.  For a more nuclear
#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
#.idea/

# PyPI configuration file
.pypirc

.vscode
```

--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------

```markdown
# MCP Server for Deepseek Integration

This repository contains a Model Control Protocol (MCP) server implementation that allows Claude Desktop to use Deepseek models running in Docker.

## Prerequisites

- Docker
- Python 3.11 or later
- A Deepseek API key
- Claude Desktop

## Installation

1. Clone the repository:

```bash
git clone https://github.com/vincentf305/mcp-server-deepseek.git
cd mcp-server-deepseek
```

2. Install dependencies:

```bash
pip install -r requirements.txt
```

## Setup Environment Variables

Create a `.env` file in the root directory of the project and add the following environment variable:

```
DEEPSEEK_API_KEY=your_api_key_here
```

Make sure to replace `your_api_key_here` with your actual Deepseek API key.

## Running the Server

### Using Docker

1. Build the Docker image:

```bash
docker build -t mcp_server_deepseek .
```

2. Run the container:

```bash
docker run -d \
  --name mcp-server-deepseek \
  -p 8765:8765 \
  -e DEEPSEEK_API_KEY=your_api_key_here \
  mcp-server-deepseek
```

### Running Locally

```bash
python -m mcp_server_deepseek.server
```

## Usage with Claude Desktop

1. Ensure you have a Deepseek API key

2. Add the following to your Claude Desktop configuration (claude_desktop_config.json):

```json
{
  "mcpServers": {
    "deepseek-server": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "DEEPSEEK_API_KEY",
        "mcp_server_deepseek"
      ],
      "env": {
        "DEEPSEEK_API_KEY": "your_api_key_here"
      }
    }
  }
}
```

3. Restart Claude Desktop to load the new configuration

## Contributing

1. Fork the repository
2. Create your feature branch (`git checkout -b feature/amazing-feature`)
3. Commit your changes (`git commit -m 'Add some amazing feature'`)
4. Push to the branch (`git push origin feature/amazing-feature`)
5. Create a Pull Request

## License

MIT License - see the [LICENSE](LICENSE) file for details

```

--------------------------------------------------------------------------------
/requirements.txt:
--------------------------------------------------------------------------------

```
requests==2.31.0
pydantic==2.10.6
pydantic-settings==2.7.1
mcp>=0.9.1
```

--------------------------------------------------------------------------------
/Dockerfile:
--------------------------------------------------------------------------------

```dockerfile
FROM python:3.13-slim

WORKDIR /app

COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

COPY mcp_server_deepseek/ ./mcp_server_deepseek/

EXPOSE 3000

CMD ["python", "-m", "mcp_server_deepseek.server"]
```

--------------------------------------------------------------------------------
/mcp_server_deepseek/config.py:
--------------------------------------------------------------------------------

```python
from pydantic_settings import BaseSettings

class Settings(BaseSettings):
    deepseek_base_url: str = "https://api.deepseek.com"
    deepseek_api_key: str = ""

    class Config:
        env_file = ".env"
        env_file_encoding = "utf-8"

settings = Settings()
```

--------------------------------------------------------------------------------
/mcp_server_deepseek/server.py:
--------------------------------------------------------------------------------

```python
import asyncio
import click
import json
import logging
import requests
import sys

import mcp
import mcp.types as types

from mcp.server import Server, NotificationOptions
from mcp.server.models import InitializationOptions

from .config import settings

logging.basicConfig(level=logging.DEBUG)
logger = logging.getLogger(__name__)

def serve() -> Server:
    server = Server("deepseek-server")

    @server.list_tools()
    async def handle_list_tools() -> list[types.Tool]:
        return [
            types.Tool(
                name="ask-deepseek",
                description="Generate responses using the Deepseek model",
                inputSchema={
                    "type": "object",
                    "properties": {
                        "messages": {
                            "type": "array",
                            "items": {
                                "type": "object",
                                "properties": {
                                    "role": {"type": "string", "enum": ["user", "assistant", "system"]},
                                    "content": {"type": "string"}
                                },
                                "required": ["role", "content"]
                            }
                        },
                        "model": {"type": "string", "default": "deepseek-coder", "enum": ["deepseek-coder", "deepseek-chat"]},
                        "temperature": {"type": "number", "default": 0.7, "minimum": 0, "maximum": 2},
                        "max_tokens": {"type": "integer", "default": 500, "minimum": 1, "maximum": 4000},
                        "top_p": {"type": "number", "default": 1.0, "minimum": 0, "maximum": 1},
                        "stream": {"type": "boolean", "default": False}
                    },
                    "required": ["messages"]
                }
            )
        ]

    @server.call_tool()
    async def handle_tool_call(name: str, arguments: dict | None) -> list[types.TextContent]:
        try:
            if not arguments:
                raise ValueError("No arguments provided")

            if name == "ask-deepseek":
                messages = arguments["messages"]
                model = arguments.get("model", "deepseek-coder")
                temperature = arguments.get("temperature", 0.7)
                max_tokens = arguments.get("max_tokens", 500)
                top_p = arguments.get("top_p", 1.0)
                stream = arguments.get("stream", False)

                deepseek_request = {
                    "model": model,
                    "messages": messages,
                    "temperature": temperature,
                    "max_tokens": max_tokens,
                    "top_p": top_p,
                    "stream": stream
                }

                json_data = json.dumps(deepseek_request)

                response = requests.post(
                    f"{settings.deepseek_base_url}/v1/chat/completions",
                    headers={
                        "Authorization": f"Bearer {settings.deepseek_api_key}",
                        "Content-Type": "application/json"
                    },
                    data=json_data
                )

                response.raise_for_status()
                data = response.json()
                chat_response = data["choices"][0]["message"]["content"]
                
                return [types.TextContent(type="text", text=chat_response)]

            raise ValueError(f"Unknown tool: {name}")
        except Exception as e:
            logger.error(f"Tool call failed: {str(e)}")
            return [types.TextContent(type="text", text=f"Error: {str(e)}")]
        
    return server

@click.command()
def main():
    try:
        async def _run():
            async with mcp.server.stdio.stdio_server() as (read_stream, write_stream):
                server = serve()
                await server.run(
                    read_stream, write_stream,
                    InitializationOptions(
                        server_name="deepseek-server",
                        server_version="0.1.0",
                        capabilities=server.get_capabilities(
                            notification_options=NotificationOptions(),
                            experimental_capabilities={}
                        )
                    )
                )
        asyncio.run(_run())
    except KeyboardInterrupt:
        logger.info("Server stopped by user")
    except Exception as e:
        logger.exception("Server failed")
        sys.exit(1)

if __name__ == "__main__":
    main()
```