Groq MCP Server

by groq

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About

A Model Context Protocol (MCP) server that provides access to Groq’s lightning-fast model inference, including chat, vision, text-to-speech, speech-to-text, batch processing, and agentic tools. It is designed for developers using MCP clients like Claude Desktop to integrate…

Details

Author
groq
GitHub stars
42
Downloads
393
Categories
Other

- Ultra-fast LLM inference with Groq models
- Vision – image analysis and understanding
- Text-to-speech (TTS) – natural speech synthesis
- Speech-to-text (STT) – transcription and translation
- Batch processing – process large workloads efficiently
- Agentic tool usage (compound-beta) for web search, code generation, and API calls

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

  1. Download and install Highlight from highlightai.com/download
  2. Navigate to the plugins tab and select "Add Custom Plugin"
  3. Configure the plugin with the settings below
    Plugin Name Groq MCP Server
    Command (node, npx, python, etc.)

    Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.

  4. Enable "Start Automatically" if you want the plugin to start when Highlight launches

From the repository

Requires a free Groq API key and Python with uv (or pip). For Claude Desktop, add the server configuration to claude_desktop_config.json using uvx groq-mcp and your API key. For other clients, install the package and run groq-mcp-config to generate configuration. Optional BASE_OUTPUT_PATH environment variable sets where generated files are saved.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "groq mcp server": {
            "groq-mcp-server": {
                "command": "uv",
                "args": [
                    "venv"
                ]
            }
        }
    }
}

McpServers

{
    "groq-mcp-server": {
        "command": "uv",
        "args": [
            "venv"
        ]
    }
}

Groq MCP Server

Query models hosted on Groq for lightning-fast inference directly from Claude and other MCP clients through the Model Context Protocol (MCP).

Use MCP to access vision models for interpreting visual data from images, instantly generate speech from text, process thousands of requests through Groq's batch processing, and even build apps with full access to Groq's documentation.

With the Groq MCP server you can try tasks like:

Agentic Tasks, Code Generation & Web Search

- What is Groq's Compound Beta? Use the compound tool. Summarize with one line then turn into voice - Please retrieve the current Bitcoin price from CoinGecko API and calculate the value of 0.38474 bitcoins? - What is the weather in SF right now? - Generate and run code, which means you can make API calls, get data from webpages, and much more - This feature uses the new compound-beta agentic tools system

Vision & Understanding

- "Describe this image [URL to image]" - "Analyze this image and extract key information as JSON [URL to image]"

Speech & Audio

- "Convert this text to speech using the Arista-PlayAI voice: [text]" - "Read this text aloud in Arabic: [text]" - "Transcribe this audio file using whisper-large-v3: [url to mp3]" - "Translate this foreign language audio to English [url to mp3]"

Batch Processing

- "Process the following batch of prompts: [location of a jsonlines file]" (read more here)

Quickstart with Claude Desktop

- Get a Groq API key for free at console.groq.com
2. Install uv (Python package manager), install with curl -LsSf https://astral.sh/uv/install.sh | sh or see the uv repo for additional install methods.
3. Go to Claude > Settings > Developer > Edit Config > claude_desktop_config.json to include the following:

{
  "mcpServers": {
    "groq": {
      "command": "uvx",
      "args": ["groq-mcp"],
      "env": {
        "GROQ_API_KEY": "your_groq_api_key",
        "BASE_OUTPUT_PATH": "/path/to/output/directory"  # Optional: Where to save generated files (default: ~/Desktop)
      }
    }
  }
}

If you're using Windows, you will have to enable "Developer Mode" in Claude Desktop to use the MCP server. Click "Help" in the hamburger menu in the top left and select "Enable Developer Mode".

If you want to install the MCP from code, scroll down to "Contributing".

Other MCP Clients

For other clients like Cursor and Windsurf:

1. Install the package:

   # Using UV (recommended)
uvx install groq-mcp

# Or using pip
pip install groq-mcp

2. Generate configuration:

   # Print config to screen
groq-mcp-config --api-key=your_groq_api_key --print

# Or save directly to config file (auto-detects location)
groq-mcp-config --api-key=your_groq_api_key

# Optional: Specify custom output path
groq-mcp-config --api-key=your_groq_api_key --output-path=/path/to/outputs

That's it! Your MCP client can now use these Groq capabilities:

- 🗣️ Text-to-Speech (TTS): Fast, natural-sounding speech synthesis
- 👂 Speech-to-Text (STT): Accurate transcription and translation
- 🖼️ Vision: Advanced image analysis and understanding
- 💬 Chat: Ultra-fast LLM inference with Llama 4 and more
- 📦 Batch: Process large workloads efficiently

Contributing

If you want to contribute or run from source:

Installation Options

Option 1: Quick Setup (Recommended)

1. Clone the repository:

   git clone https://github.com/groq/groq-mcp-server
cd groq-mcp

2. Run the setup script:

   ./scripts/setup.sh

This will:
- Create a Python virtual environment using uv
- Install all dependencies
- Set up pre-commit hooks
- Activate the virtual environment

3. Run the Claude install script:

   ./scripts/install.sh

On Macs, this will install the Groq MCP server in Claude Desktop, at ~/Library/Application Support/Claude/claude_desktop_config.json. Make sure to refresh or restart Claude Desktop.

4. Copy .env.example to .env and add your Groq API key:

   cp .env.example .env
# Edit .env and add your API key

Option 2: Manual Setup

1. Clone the repository:

   git clone https://github.com/groq/groq-mcp-server
cd groq-mcp

2. Create a virtual environment and install dependencies using uv:

   uv venv
source .venv/bin/activate
uv pip install -e ".[dev]"

3. Copy .env.example to .env and add your Groq API key:

   cp .env.example .env
# Edit .env and add your API key

Available Scripts

The scripts directory contains several utility scripts for different Groq API functionalities:

Vision & Image Analysis

```bash ./scripts/groq_vision.sh <image_file> [prompt] [temperature] [max_tokens] [output_directory]
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