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Typesense MCP Server

@avarant

リポジトリ

基本情報

カテゴリ

その他

ライセンス

MIT

トランスポート

stdio

作者

avarant

Typesense MCP Server について

MCP server for Typesense

#python#mcp#mcp-server

Typesense MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "typesense-mcp-server": {
      "command": "uv",
      "args": [
        "run",
        "python",
        "main.py"
      ],
      "env": {
        "TYPESENSE_API_KEY": "xyz"
      }
    }
  }
}

Typesense MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Typesense MCP Server?

A Model Context Protocol (MCP) server that provides a standardized interface to interact with Typesense, a fast open-source search engine. It is designed for developers using MCP-compatible clients (like Claude Desktop, Cursor, Zed, VS Code) to perform search operations, manage collections, and handle documents in Typesense through natural language commands.

How to use Typesense MCP Server?

Install uv, clone the repository to ~/typesense-mcp-server, then add the server to your MCP client’s configuration file (e.g., ~/.cursor/mcp.json or Claude Desktop config). Set the required environment variables (TYPESENSE_HOST, TYPESENSE_PORT, TYPESENSE_PROTOCOL, TYPESENSE_API_KEY). Run the server with the default STDIO transport or switch to HTTP transports for web clients.

Key features of Typesense MCP Server

  • Checks Typesense server health and lists all collections
  • Creates, describes, exports, deletes, and truncates collections
  • Creates, upserts, deletes, and batch-indexes documents
  • Imports documents from CSV data into a collection
  • Performs keyword search and vector similarity search on collections
  • Supports STDIO, legacy SSE, and Streamable HTTP transports

Use cases of Typesense MCP Server

  • Build an AI assistant that can search a Typesense-powered product catalog
  • Manage collection schemas and bulk-import documents from a conversational interface
  • Enable semantic vector search queries on text or embeddings stored in Typesense
  • Automate index maintenance tasks (e.g., truncate, export, delete) via MCP clients

よくある質問

1

How do I install the Typesense MCP Server?

Install `uv` (e.g., via Homebrew on macOS), clone the GitHub repository, then configure your MCP client to launch the server with `uv run main.py` and the required environment variables.

2

What environment variables are required?

You must set `TYPESENSE_HOST`, `TYPESENSE_PORT`, `TYPESENSE_PROTOCOL`, and `TYPESENSE_API_KEY`. Optional variables include `MCP_TRANSPORT`, `MCP_HOST`, `MCP_PORT`, `MCP_STATELESS_HTTP`, and `MCP_CORS_ORIGINS`.

3

What MCP transports does this server support?

It supports STDIO (default), legacy SSE, and the newer Streamable HTTP transport. STDIO works with desktop clients; Streamable HTTP is recommended for web-based clients.

4

Can I use this server with a web client?

Yes. Use the Streamable HTTP transport (set `MCP_TRANSPORT=streamable-http`) and enable CORS with `MCP_CORS_ORIGINS`. Stateless mode (`MCP_STATELESS_HTTP=true`) is required for clients that don’t maintain persistent MCP sessions.

5

Does this server require a running Typesense instance?

Yes. The server communicates with an existing Typesense server. You must provide its host, port, protocol, and API key via environment variables.

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