auto-mcp

# auto-mcp Automatically convert functions, tools and agents to MCP servers. ## 🧩 Installing auto-mcp You can install the SDK using PyPI or from source. ### Install within an existing project If you want to install auto-mcp as part of an existing project (e.g. to automatically convert existing agents or tools to MCP servers), it is good practice to do so within a dedicated virtual environment. #### 1. (Optional) Create a new virtual environment If you don't already have a virtual environment, create a new one using `uv`: ```bash uv init source .venv/bin/activate ``` #### 2. Add auto-mcp to your dependencies Then add auto-mcp. In `uv` this looks like: ```bash uv add auto-mcp ``` If not using `uv` or `poetry`, you can also use pip: ```bash pip install auto-mcp ``` #### 3. Initialize automcp Use the CLI to run the following command: ```bash automcp init ``` This will create an `automcp.py` file at the root of your project. #### 4. Modify the `automcp.py` file Modify the `automcp.py` file to: 1. Import the agents or tools you would like to convert from your existing project 2. Import the adapters from `automcp` that correspond to the agent framework that you are using 3. Define an input schema for the agent or tool A simple example `automcp.py` for a CrewAI agent might look like: ```python from marketing_posts.crew import MarketingPostsCrew from automcp import crewai_adapter class InputSchema(BaseModel): customer_domain: str project_description: str mcp = FastMCP("my MCP Server") name = "Marketing Crew" description = "A crew that creates marketing posts" input_schema = InputSchema tool = crewai_adapter( crewai_class=MarketingPostsCrew, name=name, description=description, input_schema=input_schema, ) mcp.add_tool( tool, name=name, description=description, ) if __name__ == "__main__": serve_stdio(mcp) # Launch the MCP server ``` #### 5. Configure your `.env` file Add any required environmental variables: ``` OPENAI_API_KEY=<your_openai_api_key> SERPER_API_KEY=<your_serper_api_key> ``` #### 6. Start the Server(s) Using STDIO: ```bash uv run serve_stdio ``` Using SSE: ```bash uv run serve_sse ``` #### 7. Testing and Integration **Cursor** Here is an example configuration of `mcp.json` that runs the MCP server using STDIO: ``` { "mcpServers": { "Marketing Crew": { "command": "uvx", "args": [ "--from", "git+https://github.com/K-Mistele/example-mcp serve_stdio" ], "env": { "OPENAI_API_KEY": "...", "SERPER_API_KEY": "..." } } } } ``` With SSE: ``` { "mcpServers": { "Marketing Crew": { "url": "http://localhost:8000/sse" } } } ``` #### 8. Publish Coming soon! ### Install from source If you are a developer contributing to AutoMCP, you will want to install from source using: ```bash git clone https://github.com/NapthaAI/auto-mcp.git cd auto-mcp uv venv source .venv/bin/activate uv pip install . ```