Anaconda MCP Server

Anaconda MCP

anaconda mcp is a CLI and server for exposing conda environment management tools to MCP-enabled AI coding assistants. It acts as a unified MCP endpoint, giving AI assistants like Claude, Cursor, and VS Code awareness of your conda environments, packages, and channel configurations.

📖 Full documentation: anaconda.com/docs · Development Guide

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Prerequisites

• Conda (Miniconda or Anaconda Distribution)

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Installation

conda create -n anaconda-mcp anaconda-mcp
conda activate anaconda-mcp

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Anaconda Login

Authentication is required. The server will not start and tool calls will not succeed without a valid Anaconda login.

anaconda login

This opens a browser for OAuth login and stores the token in your system keyring. Subsequent starts use the stored token automatically.

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Accept the Terms of Service

Anaconda MCP requires you to accept the Beta Terms before tool calls will succeed.

Interactive (recommended):

anaconda mcp terms accept

Non-interactive (CI / headless):

export ANACONDA_MCP_ACCEPTED_TERMS=true
export ANACONDA_MCP_ACCEPTED_TERMS_VERSION=2026-05-27

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Setup

Configure your AI client to use Anaconda MCP:

anaconda mcp setup

This launches an interactive wizard that detects supported clients and writes the appropriate config. Supported clients: Claude Desktop, Claude Code, Cursor, Windsurf, VS Code, and OpenCode.

To configure a specific client non-interactively:

anaconda mcp setup --client claude-code
anaconda mcp setup --client cursor --scope project

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Manual Client Configuration

If you prefer to configure your AI client manually, add an entry to your client's MCP config JSON. The anaconda mcp setup command resolves the Python path for you, but if writing by hand you'll need the full path to the environment's Python.

Example for Claude Code (.mcp.json):

{
  "mcpServers": {
    "anaconda-mcp": {
      "type": "stdio",
      "command": "/path/to/anaconda3/envs/anaconda-mcp/bin/python",
      "args": ["-m", "anaconda_mcp", "serve"],
      "env": {}
    }
  }
}

Optionally, you can pass authentication and TOS acceptance via the env dict instead of running anaconda login and anaconda mcp terms accept:

"env": {
  "ANACONDA_AUTH_API_KEY": "<your-api-key>",
  "ANACONDA_MCP_ACCEPTED_TERMS": "true",
  "ANACONDA_MCP_ACCEPTED_TERMS_VERSION": "2026-05-27"
}

API keys can be obtained from your Anaconda account settings.

⚠️ Each client has a different JSON schema. Check your client's MCP documentation carefully when writing configuration manually — field names and structure vary between Claude Code, Cursor, VS Code, and others.

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Experimental: ana CLI

The ana CLI handles Anaconda MCP runtime installation and environment setup automatically, so you don't need to manage a dedicated anaconda-mcp conda environment path.

ana mcp serve installs and runs the managed Anaconda MCP runtime. It does not install Miniconda, Anaconda Distribution, or a user-facing conda command. If you want to activate or inspect environments from a terminal, notebook, or other local tooling, install and configure conda separately for that workflow.

Install ana:

curl -fsSL https://anaconda.sh/install.sh | sh

You still need to authenticate and accept TOS by running anaconda login and anaconda mcp terms accept beforehand.

When configuring your client manually with ana, use:

{
  "mcpServers": {
    "anaconda-mcp": {
      "type": "stdio",
      "command": "ana",
      "args": ["mcp", "serve"],
      "env": {}
    }
  }
}