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Meilisearch V10 MCP Server

MCP Server generated by mcp.ag2.ai

Installation

Add the following to your MCP client configuration file.

Configuration

{
  "mcpServers": {
    "ag2-mcp-servers-meilisearch-v10": {
      "command": "python",
      "args": [
        "mcp_server/main.py",
        "stdio"
      ],
      "env": {
        "CONFIG": "{\"example\": true}",
        "SECURITY": "YOUR_API_KEYS",
        "CONFIG_PATH": "PATH_TO_CONFIG.json"
      }
    }
  }
}

This MCP server implements the Model Context Protocol for Meilisearch, enabling you to interact with your Meilisearch instance through a programmable context-aware interface. It runs locally as a stdio-based MCP server and supports development workflows, testing, and integration with MCP clients.

How to use

You connect to the MCP server from an MCP client to perform context-aware operations against Meilisearch. Start the server in stdio mode to run it as a local process and interact via standard input/output. Use the client to send MCP requests and receive structured responses that reflect the Meilisearch state and actions.

How to install

Prerequisites: Python 3.9 or newer is required. Ensure you have pip and uv installed on your system.

Step 1: Install Python dependencies for development.

pip install -e ".[dev]"

Alternatively, you can install dependencies using uv as the package manager for editable development installs.

uv pip install --editable ".[dev]"

Step 2: Run the MCP server in stdio mode.

python mcp_server/main.py stdio

Environment variables that customize the server behavior include CONFIG_PATH (path to a JSON configuration file), CONFIG (JSON string configuration), and SECURITY (security-related parameters such as API keys). Use these in your local development setup as needed.

Additional configuration and notes

Configuration details available at runtime are determined by the environment variables you supply. The server reads configuration via the CONFIG_PATH or CONFIG variables, and security parameters can be provided through SECURITY.

Development tooling includes linting, static analysis, and testing to ensure code quality during changes.

ruff check

ruff format

./scripts/static-analysis.sh

Available tools

lint

Check code quality and formatting with lints, primarily using ruff.

format

Automatically format code with ruff format to maintain consistent styling.

static-analysis

Run static risk and quality checks including mypy, bandit, and semgrep to catch type errors and security issues.

test

Execute the test suite with pytest to verify functionality and generate coverage reports.