What data does apm-mcp-server use?
It uses the Agile Practice Map knowledge base (https://www.agile-studio.jp/agile-practice-map) stored as a local Chroma DB vector database in the `data/` directory.
@HappymanOkajima
Basic information
アジャイルプラクティスマップのナレッジと対話するためのMCPサーバーです。
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"apm-mcp-server": {
"disabled": false,
"timeout": 60,
"command": "c:\\YOUR_UV_PATH\\uv",
"args": [
"--directory",
"C:\\YOUR_SERVER_INSTALL_PATH\\apm-mcp-server",
"run",
"-m",
"apm_mcp_server"
],
"transportType": "stdio"
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
apm-mcp-server is an MCP server that lets large language models query the Agile Practice Map knowledge base. It serves users who need programmatic access to agile practice information through natural language questions or list retrieval.
Install Python and the uv package manager, then clone the repository and set an OpenAI API key in a .env file. Configure your MCP client (e.g., Claude Desktop) to run the server with uv run -m apm_mcp_server or via Docker. Use the query_apm tool to ask questions and list_apm_practices to get all practice names. A pre-built Chroma DB vector database is included for immediate use.
It uses the Agile Practice Map knowledge base (https://www.agile-studio.jp/agile-practice-map) stored as a local Chroma DB vector database in the `data/` directory.
Install `uv`, clone the repository, set `OPENAI_API_KEY` in a `.env` file, then configure your MCP client to run `uv run -m apm_mcp_server` from the project directory. Docker build instructions are also provided.
Yes, it requires an OpenAI API key for generating answers via the large language model. The key must be set in the `.env` file or passed as an environment variable in the Docker configuration.
Yes. The included `populate_db.py` script can build a vector database from a web page URL or a text file, allowing you to add custom knowledge to the server.
The server uses stdio transport, as configured in MCP client json files (e.g., `claude_desktop_config.json`). Docker mode also relies on stdio communication.
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