Lenses
Manage, explore, transform and join data across multiple clusters using different flavours of Apache Kafka via Lenses.io (including the free Community Edition)
🌊🔍 Lenses MCP Server for Apache Kafka 🔎🌊
This is the Lenses MCP (Model Context Protocol) server for Apache Kafka. Lenses offers a developer experience solution for engineers building real-time applications connected to Kafka. It's built for the enterprise and backed by a powerful IAM and governance model.
With Lenses, you can find, explore, transform, integrate and replicate data across a multi-Kafka and vendor estate. Now, all this power is accessible through your AI Assistant or Agent via this Lenses MCP Server for Kafka.
See it explained and in action whilst walking through the streets of New York city!
Try it today with the free Lenses Community Edition (restricted by number of users and enterprise features). Lenses CE comes with a pre-configured single broker Kafka cluster, ideal for local development or demonstration. Connect up to two of your own Kafka clusters and then use natural language to interact with your streaming data.
Table of Contents
- 1. Install uv and Python
- 2. Configure Environment Variables
- 3. Add Lenses API Key
- 4. Install Dependencies and Run the Server
- 5. Optional Context7 MCP Server
- 6. Running with Docker
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_PORTLENSES_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 .
Máy chủ liên quan
Scout Monitoring MCP
nhà tài trợPut performance and error data directly in the hands of your AI assistant.
Alpha Vantage MCP Server
nhà tài trợAccess financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
sqlew
ADR (Architecture Decision Record) for AI Agents – An MCP server that enables AI agents to create, query, and maintain architecture decision records in a structured SQL database
GodotIQ
The intelligent MCP server for AI-assisted Godot 4 development. 35 tools for spatial intelligence, code understanding, flow tracing, and visual debugging. 22 free, full suite $19.
Jetbrains Debugger MCP Plugin
Allows AI assistants to remotely drive the JetBrains debugger via MCP, including breakpoints, stepping, and variable inspection.
Advanced Gemini MCP Server
An open-source MCP server that integrates with Google's Gemini AI. Requires a Google Gemini API key.
MCP LLaMA
An MCP server with weather tools and LLaMA integration.
Vibe Coder
An advanced MCP server for semantic routing, code generation, workflows, and AI-assisted development.
YFinance Trader
Provides stock market data and trading capabilities using the yfinance library.
Test Code Generator
Generates Vitest test code from JSON specifications using boundary value analysis and equivalence partitioning.
Remote MCP Server (Authless)
An example of a remote MCP server without authentication, deployable on Cloudflare Workers.
Webhook Tester MCP Server
Interact with webhook-test.com to automate and manage webhook tokens, inspect incoming requests, and perform analytics.