Meilisearch MCP Server

Meilisearch MCP Server

Enables AI assistants to interact with Meilisearch via the Model Context Protocol, allowing comprehensive index, document, and search management through a standardized interface.

Category
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Tools

list-indexes

List all indexes in the Meilisearch instance

get-index

Get information about a specific Meilisearch index

create-index

Create a new Meilisearch index

update-index

Update a Meilisearch index (currently only supports updating the primary key)

delete-index

Delete a Meilisearch index

swap-indexes

Swap two or more indexes in Meilisearch

get-documents

Get documents from a Meilisearch index

get-document

Get a document by its ID from a Meilisearch index

add-documents

Add documents to a Meilisearch index

update-documents

Update documents in a Meilisearch index

delete-documents

Delete multiple documents by their IDs from a Meilisearch index

delete-document

Delete a document by its ID from a Meilisearch index

delete-all-documents

Delete all documents in a Meilisearch index

search

Search for documents in a Meilisearch index

multi-search

Perform multiple searches in one request

facet-search

Search for facet values matching specific criteria

get-settings

Get all settings for a Meilisearch index

update-settings

Update settings for a Meilisearch index

reset-settings

Reset all settings for a Meilisearch index to their default values

get-searchable-attributes

Get the searchable attributes setting

get-displayed-attributes

Get the displayed attributes setting

get-filterable-attributes

Get the filterable attributes setting

get-sortable-attributes

Get the sortable attributes setting

get-ranking-rules

Get the ranking rules setting

get-stop-words

Get the stop words setting

get-synonyms

Get the synonyms setting

get-distinct-attribute

Get the distinct attribute setting

get-typo-tolerance

Get the typo tolerance setting

get-faceting

Get the faceting setting

get-pagination

Get the pagination setting

update-searchable-attributes

Update the searchable attributes setting

update-displayed-attributes

Update the displayed attributes setting

update-filterable-attributes

Update the filterable attributes setting

update-sortable-attributes

Update the sortable attributes setting

update-ranking-rules

Update the ranking rules setting

update-stop-words

Update the stop words setting

update-synonyms

Update the synonyms setting

update-distinct-attribute

Update the distinct attribute setting

update-typo-tolerance

Update the typo tolerance setting

update-faceting

Update the faceting setting

update-pagination

Update the pagination setting

reset-searchable-attributes

Reset the searchable attributes setting to its default value

reset-displayed-attributes

Reset the displayed attributes setting to its default value

reset-filterable-attributes

Reset the filterable attributes setting to its default value

reset-sortable-attributes

Reset the sortable attributes setting to its default value

reset-distinct-attribute

Reset the distinct attribute setting to its default value

reset-typo-tolerance

Reset the typo tolerance setting to its default value

reset-faceting

Reset the faceting setting to its default value

reset-ranking-rules

Reset the ranking rules setting to its default value

reset-stop-words

Reset the stop words setting to its default value

reset-synonyms

Reset the synonyms setting to its default value

reset-pagination

Reset the pagination setting to its default value

enable-vector-search

Enable the vector search experimental feature in Meilisearch

get-experimental-features

Get the status of experimental features in Meilisearch

update-embedders

Configure embedders for vector search

get-embedders

Get the embedders configuration for an index

reset-embedders

Reset the embedders configuration for an index

vector-search

Perform a vector search in a Meilisearch index

health

Check if the Meilisearch server is healthy

version

Get the version information of the Meilisearch server

info

Get the system information of the Meilisearch server

stats

Get statistics about all indexes or a specific index

get-tasks

Get information about tasks with optional filtering

delete-tasks

Delete tasks based on provided filters

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

README

Meilisearch MCP Server

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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

  1. Clone the repository:

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

    npm install
    
  3. Create a .env file based on the example:

    cp .env.example .env
    
  4. 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:

  1. Create a .env file from .env.example if it doesn't exist
  2. Install dependencies
  3. Build the project
  4. 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:

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

Manual Setup

If you prefer to manually configure Claude for Desktop:

  1. 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
  2. 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"
      }
    }
  }
}
  1. Restart Claude for Desktop to apply the changes.

  2. 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

  1. 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
    
  2. Start the MCP server:

    npm start
    
  3. In Cursor, open the Command Palette (Cmd/Ctrl+Shift+P) and search for "MCP: Connect to MCP Server".

  4. 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
      
  5. Click "Connect" to establish the connection.

  6. 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

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