What are the runtime dependencies?
Python 3, a virtual environment, and packages listed in `requirements.txt`. The server uses SQLite locally and requires no external database.
@soapko
Basic information
A lightweight, local server designed to support agile task workflows within AI coding environments using the Model Context Protocol (MCP).
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"alice-mcp-server": {
"command": "python",
"args": [
"-m",
"venv",
"venv"
]
}
}
}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.
Alice MCP - Agile Task Management is a lightweight, local server that supports agile task workflows within AI coding environments using the Model Context Protocol (MCP). It provides a backend for managing projects, tasks, epics, and messages locally on your machine, with project isolation to support multiple distinct software projects.
Clone the repository, create and activate a Python virtual environment, and install dependencies from requirements.txt. You can run the server automatically via the provided scripts/start-alice-servers.sh wrapper script, or manually by starting the FastAPI backend with uvicorn app.main:app --reload. When using the MCP server tools, provide the project’s name (string) as the project_id argument; for direct API calls, use the internal numeric project ID.
Python 3, a virtual environment, and packages listed in `requirements.txt`. The server uses SQLite locally and requires no external database.
Direct API endpoints use numeric project IDs in URL paths (e.g., `/1/tasks/`). When using the MCP server tools, you provide the project’s name as `project_id`, and the MCP server resolves it to the internal numeric ID.
All data is stored locally in a SQLite database file. No data is sent to external servers.
While the server is running, interactive API documentation is available at `http://127.0.0.1:8000/docs` (Swagger UI) or `http://127.0.0.1:8000/redoc` (ReDoc). You can also send direct HTTP requests to the endpoints listed in the README.
The README does not mention any authentication mechanism. The server runs locally on `127.0.0.1:8000` by default.

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