Meilisearch MCP Server
Enables AI assistants to interact with Meilisearch through a standardized interface, supporting index and document management, search capabilities, settings configuration, task monitoring, and experimental vector search.
README
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
.envfile based on the example:cp .env.example .env -
Edit the
.envfile 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
.envfile from.env.exampleif 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
.envfile - 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
- macOS:
-
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 indexget-index: Get information about an indexlist-indexes: List all indexesupdate-index: Update an indexdelete-index: Delete an index
Document Tools
add-documents: Add documents to an indexget-document: Get a document by IDget-documents: Get multiple documentsupdate-documents: Update documentsdelete-document: Delete a document by IDdelete-documents: Delete multiple documentsdelete-all-documents: Delete all documents in an index
Search Tools
search: Search for documentsmulti-search: Perform multiple searches in a single request
Settings Tools
get-settings: Get index settingsupdate-settings: Update index settingsreset-settings: Reset index settings to default- Various specific settings tools (synonyms, stop words, ranking rules, etc.)
Task Tools
list-tasks: List tasks with optional filteringget-task: Get information about a specific taskcancel-tasks: Cancel tasks based on provided filterswait-for-task: Wait for a specific task to complete
System Tools
health: Check the health status of the Meilisearch serverversion: Get version informationinfo: Get system informationstats: Get statistics about indexes
Vector Tools (Experimental)
enable-vector-search: Enable vector searchget-experimental-features: Get experimental features statusupdate-embedders: Configure embeddersget-embedders: Get embedders configurationreset-embedders: Reset embedders configurationvector-search: Perform vector search
License
MIT
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。