Simple MCP Ollama Bridge

MCP LLM桥

连接模型上下文协议（MCP）服务器和Ollama等OpenAI兼容LLM的桥梁 点击此处阅读更多关于Anthropic的MCP：

• 资源
• 鼓励
• 工具
• 采样

快速开始

# Install
curl -LsSf https://astral.sh/uv/install.sh | sh
git clone https://github.com/bartolli/mcp-llm-bridge.git
cd mcp-llm-bridge
uv venv
source .venv/bin/activate
uv pip install -e .

Note: reactivate the environment if needed to use the keys in `.env`: `source .venv/bin/activate`

Then configure the bridge in [src/mcp_llm_bridge/main.py](src/mcp_llm_bridge/main.py)

mcp_server_params=StdioServerParameters( command="uv", # CHANGE THIS = it needs to be an absolute directory! add the mcp fetch server at the directory (clone from https://github.com/modelcontextprotocol/servers/) args=["--directory", "~/llms/mcp/mc-server-fetch/servers/src/fetch", "run", "mcp-server-fetch"], env=None ), # llm_config=LLMConfig( # api_key=os.getenv("OPENAI_API_KEY"), # model=os.getenv("OPENAI_MODEL", "gpt-4o"), # base_url=None # ), llm_config=LLMConfig( api_key="ollama", # Can be any string for local testing model="llama3.2", base_url="http://localhost:11434/v1" # Point to your local model's endpoint ), )

### 附加端点支持

该网桥还与实现OpenAI API规范的任何端点一起工作：

#### 没有

llm_config=LLMConfig( api_key="not-needed", model="mistral-nemo:12b-instruct-2407-q8_0", base_url="http://localhost:11434/v1" )

## 许可证

[麻省理工学院](LICENSE.md)

## 贡献

PR欢迎。