Lenses MCP Server

Lenses MCP Server

Manage, explore, transform and join data in Kafka topics across multiple clusters using different flavours of Apache Kafka via Lenses.io (including the free Community Edition)

Category
访问服务器

README

🌊🔍 Lenses MCP Server 🔎🌊

This is the MCP (Model Context Protocol) server for Lenses, a self-service DataOps tool for engineers building real-time applications with different flavours of Apache Kafka across multiple clusters. Explore, transform and join data in topics from different clusters using SQL, without the need for an additional database.

Try this with the free Lenses Community Edition (restricted by number of users and enterprise features, e.g. OAuth). Requires Lenses v6+.

Table of Contents

1. Install uv and Python

We use uv for dependency management and project setup. If you don't have uv installed, follow the official installation guide.

This project has been built using Python 3.12 and to make sure Python is correctly installed, run the following command to check the version.

uv run python --version

2. Configure Environment Variables

Copy the example environment file.

cp .env.example .env

Open .env and fill in the required values such as your Lenses instance details and Lenses API key.

3. Add Lenses API Key

Create a Lenses API key by creating an IAM Service Account. Add the API key to .env with the variable name, LENSES_API_KEY.

4. Install Dependencies and Run the Server

Use uv to create a virtual environment, install the project dependencies in it and then run the MCP server with the FastMCP CLI using the default stdio transport.

uv sync
uv run src/lenses_mcp/server.py

To run as a remote server, use the http transport.

uv run fastmcp run src/lenses_mcp/server.py --transport=http --port=8000

To run in Claude Desktop, Gemini CLI, Cursor, etc. use the following JSON configuration.

{
  "mcpServers": {
    "Lenses.io": {
      "command": "uv",
      "args": [
        "run",
        "--project", "<ABSOLUTE_PATH_TO_THIS_REPO>",
        "--with", "fastmcp",
        "fastmcp",
        "run",
        "<ABSOLUTE_PATH_TO_THIS_REPO>/src/lenses_mcp/server.py"
      ],
      "env": {
        "LENSES_API_KEY": "<YOUR_LENSES_API_KEY>"
      },
      "transport": "stdio"
    }
  }
}

Note: Some clients may require the absolute path to uv in the command.

5. Optional Context7 MCP Server

Lenses documentation is available on Context7. It is optional but highly recommended to use the Context7 MCP Server and adjust your prompts with use context7 to ensure the documentation available to the LLM is up to date.

6. Running with Docker

The Lenses MCP server is available as a Docker image at lensesio/mcp. You can run it with different transport modes depending on your use case.

Quick Start

Run the server with stdio transport (default):

docker run \
   -e LENSES_API_KEY=<YOUR_API_KEY> \
   -e LENSES_URL=http://localhost:9991 \
   lensesio/mcp

Run the server with HTTP transport (listens on http://0.0.0.0:8000/mcp):

docker run -p 8000:8000 \
   -e LENSES_API_KEY=<YOUR_API_KEY> \
   -e LENSES_URL=http://localhost:9991 \
   -e TRANSPORT=http \
   lensesio/mcp

Run the server with SSE transport (listens on http://0.0.0.0:8000/sse):

docker run -p 8000:8000 \
   -e LENSES_API_KEY=<YOUR_API_KEY> \
   -e LENSES_URL=http://localhost:9991 \
   -e TRANSPORT=sse \
   lensesio/mcp

Environment Variables

Variable Required Default Description
LENSES_API_KEY Yes - Your Lenses API key (create via IAM Service Account)
LENSES_URL No http://localhost:9991 Lenses instance URL in format [scheme]://[host]:[port]. Use https:// for secure connections (automatically uses wss:// for WebSockets)
TRANSPORT No stdio Transport mode: stdio, http, or sse
PORT No 8000 Port to listen on (only used with http or sse transport)

Legacy environment variables (for backward compatibility):

  • LENSES_API_HTTP_URL, LENSES_API_HTTP_PORT
  • LENSES_API_WEBSOCKET_URL, LENSES_API_WEBSOCKET_PORT

These are automatically derived from LENSES_URL but can be explicitly set to override.

Transport Endpoints

  • stdio: Standard input/output (no network endpoint)
  • http: HTTP endpoint at /mcp
  • sse: Server-Sent Events endpoint at /sse

Building the Docker Image

To build the Docker image locally:

docker build -t lensesio/mcp .

推荐服务器

Baidu Map

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。

官方
精选
JavaScript
Playwright MCP Server

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。

官方
精选
TypeScript
Magic Component Platform (MCP)

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。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

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。

官方
精选
本地
TypeScript
VeyraX

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。

官方
精选
本地
graphlit-mcp-server

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。

官方
精选
TypeScript
Kagi MCP Server

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。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

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。

官方
精选