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 🔎🌊
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
- 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 .
Related Servers
Scout Monitoring MCP
sponsorPut performance and error data directly in the hands of your AI assistant.
Alpha Vantage MCP Server
sponsorAccess financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
PostHog MCP
Integrates with PostHog for feature flag management and error tracking.
MCP VSCode Cline
A guide for using the Cline VSCode extension to interact with Model Context Protocol (MCP) servers.
Gentoro
Gentoro generates MCP Servers based on OpenAPI specifications.
Bevy BRP MCP
Control, inspect, and mutate Bevy applications with AI coding assistants via the Bevy Remote Protocol (BRP).
Shell Executor
Execute shell commands safely on a remote server.
Claude Code Exporter
Export and organize Claude Code conversations with powerful filtering. Supports CLI and MCP server integration for Claude Desktop.
MCP-guide
A guide for setting up an MCP server using a Python virtual environment and integrating it with the Cline VS Code extension.
Ghibli Video
Generates AI images and videos using the GPT4O Image Generator API.
Authless Remote MCP Server
An authless remote MCP server designed for deployment on Cloudflare Workers. It can be set up locally using npm create.
Synth MCP
Access financial data like stock prices, currency info, and insider trading data using the Synth Finance API.