conda-meta-mcp

An MCP (Model Context Protocol) server exposing authoritative, read-only Conda ecosystem metadata for AI agents.

What “Meta” Means Here

“Meta” refers to structured, machine-consumable ecosystem intelligence about packages — not the upstream project documentation itself. This server provides (see also the schema server-info.json for current capabilities):

Currently available:

• Version metadata (MCP tool/library versions) via the info tool
• Package info tarball data via the package_insights tool
• Package search via the package_search tool
• Import to package heuristic mapping via the import_mapping tool
• PyPI name to conda package mapping via the pypi_to_conda tool
• CLI help (for conda) via the cli_help tool
• Repository metadata queries (depends / whoneeds) via the repoquery tool

Planned:

• Solver feasibility signals (dry-run outputs)
• Schema references and selected spec excerpts
• Binary linkage information
• Links (not copies) to sections of knowledge bases

It does not embed, index, or serve full library docs (e.g. numpy API pages); that remains out of scope by design.

1. Purpose

Enable agents to answer packaging questions by providing up-to-date critical and fragmented expert knowledge. This project provides a safe, inspectable, zero‑side‑effect surface so agents deliver accurate, up‑to‑date guidance.

2. Scope

Goals

• Trustworthy machine interface
• Read‑only, hostable
• Fast startup, low latency
• Clear extension & testing pattern

Non‑Goals

• Performing installs / mutations
• Replacing human docs
• Re‑implementing conda‑forge processing logic

3. Design Principles

• Side‑effect free by contract
• Tool registration pattern (conda_meta_mcp.tools)
• Test + pre‑commit enforced consistency
• Incremental expansion

4. Quick Start

Prerequisites: pixi

git clone https://github.com/conda-incubator/conda-meta-mcp.git
cd conda-meta-mcp
pixi run cmm --help

The pixi command can be used to run the MCP locally in clients such as VSCode, Cursor, Claude Desktop, Goose and Zed:

{
  "conda-meta-mcp": {
    "command": "pixi",
    "args": [
      "run",
      "--manifest-path",
      "/path/to/pyproject.toml",
      "cmm",
      "run",
      "-v"
    ],
    "env": {}
  }
}

Or call pixi run cmm mcp-json, which emits a JSON snippet with absolute paths that can be pasted into an MCP client configuration.

5. Usage inside GitHub Copilot coding agent

Create a GitHub workflow named copilot-setup-steps.yml containing (see also GitHub Documentation):

jobs:
  copilot-setup-steps:
    ...
    steps:
      ...
      - name: Setup conda-meta-mcp
        uses: conda-incubator/conda-meta-mcp@main
      ...

Add this MCP configuration inside your repository under Settings -> Copilot -> Coding agent -> MCP Configuration:

{
  "mcpServers": {
    "conda-meta-mcp": {
      "type": "local",
      "command": "cmm",
      "args": [
        "run"
      ],
      "tools": [
        "*"
      ]
    }
  }
}

6. Development

Tasks (pixi):

• Tests: pixi run test (for coverage open htmlcov/index.html)
• Lint / format / type / regenerate metadata: pixi run pre-commit

7. Extending (New Tool)

1. Add conda_meta_mcp/tools/<name>.py (see existing tools)
2. Implement register_<name> with an @mcp.tool async function
3. Append to TOOLS in tools/__init__.py
4. Add unit tests (mock heavy deps)
5. pixi run pre-commit
6. pixi run test
7. Open PR

8. Safety Model

• No environment mutation
• No external command side effects
• Future additions must preserve read‑only contract