Meilisearch MCP Server

A Model Context Protocol (MCP) server implementation for Meilisearch, enabling AI assistants to interact with Meilisearch through a standardized interface.

Features

Index Management: Create, update, and delete indexes
Document Management: Add, update, and delete documents
Search Capabilities: Perform searches with various parameters and filters
Settings Management: Configure index settings
Task Management: Monitor and manage asynchronous tasks
System Operations: Health checks, version information, and statistics
Vector Search: Experimental vector search capabilities

Installation

Installing via Smithery

To install Meilisearch MCP Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @devlimelabs/meilisearch-ts-mcp --client claude

Manual Installation

Clone the repository:

git clone https://github.com/devlimelabs/meilisearch-ts-mcp.git
cd meilisearch-ts-mcp

Install dependencies:
```
npm install
```
Create a .env file based on the example:
```
cp .env.example .env
```
Edit the .env file to configure your Meilisearch connection.

Docker Setup

The Meilisearch MCP Server can be run in a Docker container for easier deployment and isolation.

Using Docker Compose

The easiest way to get started with Docker is to use Docker Compose:

# Start the Meilisearch MCP Server
docker-compose up -d

# View logs
docker-compose logs -f

# Stop the server
docker-compose down

Building and Running the Docker Image Manually

You can also build and run the Docker image manually:

# Build the Docker image
docker build -t meilisearch-ts-mcp .

# Run the container
docker run -p 3000:3000 --env-file .env meilisearch-ts-mcp

Development Setup

For developers who want to contribute to the Meilisearch MCP Server, we provide a convenient setup script:

# Clone the repository
git clone https://github.com/devlimelabs-ts-mcp/meilisearch-ts-mcp.git
cd meilisearch-ts-mcp

# Run the development setup script
./scripts/setup-dev.sh

The setup script will:

Create a .env file from .env.example if it doesn't exist
Install dependencies
Build the project
Run tests to ensure everything is working correctly

After running the setup script, you can start the server in development mode:

npm run dev

Usage

Building the Project

npm run build

Running the Server

npm start

Development Mode

npm run dev

Claude Desktop Integration

The Meilisearch MCP Server can be integrated with Claude for Desktop, allowing you to interact with your Meilisearch instance directly through Claude.

Automated Setup

We provide a setup script that automatically configures Claude for Desktop to work with the Meilisearch MCP Server:

# First build the project
npm run build

# Then run the setup script
node scripts/claude-desktop-setup.js

The script will:

Detect your operating system and locate the Claude for Desktop configuration file
Read your Meilisearch configuration from the .env file
Generate the necessary configuration for Claude for Desktop
Provide instructions for updating your Claude for Desktop configuration

Manual Setup

If you prefer to manually configure Claude for Desktop:

Locate your Claude for Desktop configuration file:
- macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
- Windows: %APPDATA%\Claude\claude_desktop_config.json
- Linux: ~/.config/Claude/claude_desktop_config.json
Add the following configuration (adjust paths as needed):

{
  "mcpServers": {
    "meilisearch": {
      "command": "node",
      "args": ["/path/to/meilisearch-ts-mcp/dist/index.js"],
      "env": {
        "MEILISEARCH_HOST": "http://localhost:7700",
        "MEILISEARCH_API_KEY": "your-api-key"
      }
    }
  }
}

Restart Claude for Desktop to apply the changes.
In Claude, type: "I want to use the Meilisearch MCP server" to activate the integration.

Cursor Integration

The Meilisearch MCP Server can also be integrated with Cursor, an AI-powered code editor.

Setting Up MCP in Cursor

Install and set up the Meilisearch MCP Server:

git clone https://github.com/devlimelabs/meilisearch-ts-mcp.git
cd meilisearch-ts-mcp
npm install
npm run build

Start the MCP server:
```
npm start
```
In Cursor, open the Command Palette (Cmd/Ctrl+Shift+P) and search for "MCP: Connect to MCP Server".
Select "Connect to a local MCP server" and enter the following details:
- Name: Meilisearch
- Command: node
- Arguments: /absolute/path/to/meilisearch-ts-mcp/dist/index.js
- Environment Variables:
```
MEILISEARCH_HOST=http://localhost:7700
MEILISEARCH_API_KEY=your-api-key
```
Click "Connect" to establish the connection.
You can now interact with your Meilisearch instance through Cursor by typing commands like "Search my Meilisearch index for documents about..."

Available Tools

The Meilisearch MCP Server provides the following tools:

Index Tools

create-index: Create a new index
get-index: Get information about an index
list-indexes: List all indexes
update-index: Update an index
delete-index: Delete an index

Document Tools

add-documents: Add documents to an index
get-document: Get a document by ID
get-documents: Get multiple documents
update-documents: Update documents
delete-document: Delete a document by ID
delete-documents: Delete multiple documents
delete-all-documents: Delete all documents in an index

Search Tools

search: Search for documents
multi-search: Perform multiple searches in a single request

Settings Tools

get-settings: Get index settings
update-settings: Update index settings
reset-settings: Reset index settings to default
Various specific settings tools (synonyms, stop words, ranking rules, etc.)

Task Tools

list-tasks: List tasks with optional filtering
get-task: Get information about a specific task
cancel-tasks: Cancel tasks based on provided filters
wait-for-task: Wait for a specific task to complete

System Tools

health: Check the health status of the Meilisearch server
version: Get version information
info: Get system information
stats: Get statistics about indexes

Vector Tools (Experimental)

enable-vector-search: Enable vector search
get-experimental-features: Get experimental features status
update-embedders: Configure embedders
get-embedders: Get embedders configuration
reset-embedders: Reset embedders configuration
vector-search: Perform vector search

License

MIT

Meilisearch Integration