# Clone the repository
git clone https://github.com/esakrissa/mcp-doc.git
cd mcp-doc

# Create and activate a virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install the package in development mode
pip install -e .

# Run the server with the config file
mcpdoc \
    --json config.json \
    --transport sse \
    --port 8082 \
    --host localhost

# Install uv (if not already installed)
curl -LsSf https://astral.sh/uv/install.sh | sh

# Run the server with UV
uvx --from mcpdoc mcpdoc \
    --json config.json \
    --transport sse \
    --port 8082 \
    --host localhost

{
  "mcpServers": {
    "mcp-doc": {
      "command": "uvx",
      "args": [
        "--from",
        "mcpdoc",
        "mcpdoc",
        "--urls",
        "LangGraph:https://raw.githubusercontent.com/esakrissa/mcp-doc/main/docs/langgraph.txt",
        "ModelContextProtocol:https://raw.githubusercontent.com/esakrissa/mcp-doc/main/docs/mcp.txt",
        "--allowed-domains",
        "*",
        "--transport",
        "stdio"
      ]
    }
  }
}

for ANY question about LangGraph and Model Context Protocol (MCP), use the mcp-doc server to help answer -- 
+ call list_doc_sources tool to get the available documentation files
+ call fetch_docs tool to read the langgraph.txt or mcp.txt file
+ reflect on the urls in langgraph.txt or mcp.txt 
+ reflect on the input question 
+ call fetch_docs on any urls relevant to the question
+ use this to answer the question