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:
- 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
- "Describe this image [URL to image]"
- "Analyze this image and extract key information as JSON [URL to image]"
- "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]"
- "Process the following batch of prompts: [location of a jsonlines file]" (read more here)
- Get a Groq API key for free at console.groq.com
- Install
uv
(Python package manager), install withcurl -LsSf https://astral.sh/uv/install.sh | sh
or see theuv
repo for additional install methods. - 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".
For other clients like Cursor and Windsurf:
-
Install the package:
# Using UV (recommended) uvx install groq-mcp # Or using pip pip install groq-mcp
-
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
If you want to contribute or run from source:
-
Clone the repository:
git clone https://github.com/groq/groq-mcp-server cd groq-mcp
-
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
- Create a Python virtual environment using
-
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. -
Copy
.env.example
to.env
and add your Groq API key:cp .env.example .env # Edit .env and add your API key
-
Clone the repository:
git clone https://github.com/groq/groq-mcp-server cd groq-mcp
-
Create a virtual environment and install dependencies using uv:
uv venv source .venv/bin/activate uv pip install -e ".[dev]"
-
Copy
.env.example
to.env
and add your Groq API key:cp .env.example .env # Edit .env and add your API key
The scripts
directory contains several utility scripts for different Groq API functionalities:
./scripts/groq_vision.sh <image_file> [prompt] [temperature] [max_tokens] [output_directory]
# Example:
./scripts/groq_vision.sh "./input/image.jpg" "What is in this image?"
./scripts/groq_tts.sh "Your text" [voice_name] [model] [output_directory]
# Example:
./scripts/groq_tts.sh "Hello, world!" "Arista-PlayAI"
./scripts/groq_stt.sh <audio_file> [model] [output_directory]
list_groq_voices.sh
: Display available TTS voiceslist_groq_stt_models.sh
: Show available STT modelsgroq_batch.sh
: Process batch operationsgroq_translate.sh
: Translate text or audio
# Run tests
./scripts/test.sh
# Run with options
./scripts/test.sh --verbose --fail-fast
# Run integration tests
./scripts/test.sh --integration
# Debug and test locally
mcp install server.py
mcp dev server.py
Logs when running with Claude Desktop can be found at:
- Windows:
%APPDATA%\Claude\logs\groq-mcp.log
- macOS:
~/Library/Logs/Claude/groq-mcp.log
This project is inspired by the ElevenLabs MCP Server. Thanks!