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Groq MCP Server for Claude

Query Groq's ultra-fast inference models from Claude — vision, text-to-speech, speech-to-text, batch processing, and agentic compound-beta tools with web search and code execution — using the official Groq Model Context Protocol server.

by Groq·added 2026-06-18·

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Install

Source

claude mcp add groq -e GROQ_API_KEY=your-api-key -- uvx groq-mcp

Readiness

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ReviewedYes

Documentation Source repository Registry JSON · LLM text

Review first — review before installing

Open the source and read safety notes before installing.

Safety notes

The `compound-beta` tools include code execution and live web search — code runs in Groq's sandboxed environment but web requests are made to external URLs.
Text-to-speech and speech-to-text outputs are saved to `BASE_OUTPUT_PATH` (default: ~/Desktop) — ensure this path has appropriate access controls.

Privacy notes

Text, images, and audio passed to Groq tools are sent to Groq's API for inference — do not pass sensitive or personally identifiable data.
Your `GROQ_API_KEY` is passed as an environment variable — treat it as a secret and store it securely.

Prerequisites

A Groq API key (free at console.groq.com).
Python with `uv` installed: `pip install uv` or `brew install uv`.
An MCP client such as Claude Code or Claude Desktop.

Schema details

Install type: cli
Troubleshooting: No

Source repository stats

Scope: Source repo

Collection metadata

Estimated setup: 5 minutes
Difficulty: beginner

Tool listing metadata

Website: https://console.groq.com
Disclosure: Groq is a commercial AI inference provider. The MCP server is officially maintained by Groq.

Full copyable content

{
  "mcpServers": {
    "groq": {
      "command": "uvx",
      "args": ["groq-mcp"],
      "env": {
        "GROQ_API_KEY": "your-api-key"
      }
    }
  }
}

About this resource

Overview

The Groq MCP Server is the official Model Context Protocol server from Groq, the AI inference company behind GroqCloud. It lets Claude access Groq's ultra-fast inference for text generation, vision, text-to-speech, speech-to-text, and batch processing — plus the compound-beta agentic system that adds live web search and code execution to Groq model calls. Licensed under MIT.

Key capabilities

Text generation — query any Groq-hosted model (LLaMA 3, Mixtral, Gemma, DeepSeek) at Groq's low-latency speeds.
Vision — describe images, extract structured JSON, and analyze visual data using Groq's vision models.
Text-to-speech (TTS) — convert text to audio with voices from PlayAI (Arista, Atlas, etc.).
Speech-to-text (STT) — transcribe and translate audio files using whisper-large-v3.
Batch processing — process thousands of prompts from a JSONL file asynchronously.
Compound-beta — Groq's agentic tool system: web search + code execution in a single Groq inference call; can fetch live data, compute with it, and return results.
Documentation access — built-in access to Groq documentation for building applications.

How it compares

Server	Text gen	Vision	TTS/STT	Batch	Agentic tools	Inference speed
Groq MCP	Yes	Yes	Yes	Yes	Yes (compound-beta)	Ultra-fast (LPU)
OpenAI MCP	Yes	Yes	Yes	Yes	Yes (Assistants)	Standard
Anthropic MCP	Yes	Yes	No	No	No	Standard
Ollama MCP	Yes	Yes	No	No	No	Local

Groq's LPU hardware delivers inference speeds up to 10× faster than GPU-based providers, making it ideal for latency-sensitive workflows and real-time voice applications.

Installation

Claude Code

claude mcp add groq -e GROQ_API_KEY=your-api-key -- uvx groq-mcp

Get your free API key at console.groq.com.

Claude Desktop

{
  "mcpServers": {
    "groq": {
      "command": "uvx",
      "args": ["groq-mcp"],
      "env": {
        "GROQ_API_KEY": "your-api-key",
        "BASE_OUTPUT_PATH": "/path/to/outputs"
      }
    }
  }
}

Configuration generation

# Install the package
pip install groq-mcp

# Auto-generate and save configuration
groq-mcp-config --api-key=your-api-key

Requirements

A Groq API key (free tier available).
Python with uv installed (pip install uv).
An MCP client (Claude Code or Claude Desktop).

Security

Compound-beta web search and code execution are sandboxed by Groq.
TTS/STT files are saved locally to BASE_OUTPUT_PATH — keep this path private if outputs contain sensitive content.

Source Verification Notes

Verified on 2026-06-18:

Official GitHub repository groq/groq-mcp-server (MIT, 42 stars) documents the groq-mcp PyPI package installed via uvx, GROQ_API_KEY and BASE_OUTPUT_PATH configuration, vision (image analysis), TTS (PlayAI voices), STT (Whisper), batch processing (JSONL), the compound-beta agentic system (web search + code execution), and the groq-mcp-config utility for auto-generating client configs.
Claude Code MCP documentation at code.claude.com/docs/en/mcp describes the stdio connector setup pattern used above.

#groq #inference #llm #vision #speech #audio #batch-processing

Source citations

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How it compares

Groq MCP Server for Claude side by side with 3 alternatives on trust, install, platform support, and disclosed safety notes — all from reviewed registry metadata.

Field	Groq MCP Server for Claude Query Groq's ultra-fast inference models from Claude — vision, text-to-speech, speech-to-text, batch processing, and agentic compound-beta tools with web search and code execution — using the official Groq Model Context Protocol server. Open dossier	Deepgram MCP Server for Claude Transcribe audio, synthesize speech, and run audio intelligence directly from Claude with the official Deepgram MCP server — dynamic tool discovery fetches new capabilities from Deepgram's API at runtime without requiring package upgrades. Open dossier	ElevenLabs MCP Server Official ElevenLabs MCP server for generating speech, designing voices, cloning voices, transcribing audio, creating sound effects, and working with conversational audio agents through the ElevenLabs API. Open dossier	FunASR MCP Server MCP server example from FunASR that lets Claude transcribe local audio files with local speech recognition, automatic language handling, timestamps, and speaker labels when available. Open dossier
Trust
Install risk	Review first	Review first	Review first	Review first
Notes	Safety ✓ Privacy ✓	Safety ✓ Privacy ✓	Safety ✓ Privacy ✓	Safety ✓ Privacy ✓
Category	mcp	mcp	mcp	mcp
Source	source-backed	source-backed	source-backed	source-backed
Author	Groq	Deepgram	ElevenLabs	FunASR
Added	2026-06-18	2026-06-18	2026-06-06	2026-06-06
Platforms	Claude CodeCodexCursorClaude Desktop	Claude CodeClaude Desktop	Claude CodeClaude Desktop	Claude CodeClaude Desktop
Source repo	—	—	—	—
Safety notes	✓The `compound-beta` tools include code execution and live web search — code runs in Groq's sandboxed environment but web requests are made to external URLs. Text-to-speech and speech-to-text outputs are saved to `BASE_OUTPUT_PATH` (default: ~/Desktop) — ensure this path has appropriate access controls.	✓Audio files and transcription payloads are sent to Deepgram's cloud API for processing — do not transcribe audio containing highly sensitive PII without reviewing Deepgram's data retention policies. Text-to-speech outputs are returned as audio data via the API; no files are written to disk unless you explicitly save them.	✓ElevenLabs MCP Server can call paid ElevenLabs API endpoints; text-to-speech, voice design, voice cloning, audio isolation, transcription, sound generation, music, and agent workflows can consume account credits. Voice cloning and voice conversion can create realistic synthetic speech, so require documented consent and review before processing a person's voice or publishing generated audio. Generated speech, sound effects, music, transcripts, and conversation-agent configuration can affect public-facing content; review prompts, voice IDs, output format, language, and destination before publishing or sending. File output mode writes generated files to disk under the configured base path; restrict that path to an approved directory and avoid broad home, desktop, or shared folders in production. Use separate API keys or workspaces for test and production clients, monitor credit usage, and disable tools in clients that should not spend credits. Some operations may take longer than normal MCP tool timeouts; do not retry expensive generation calls blindly.	✓The MCP server exposes a `transcribe_audio` tool that reads the local file path supplied by the agent. Configure clients so Claude can only request audio files from approved directories; do not expose arbitrary private folders or shared drives. First use can download FunASR model weights and dependencies from upstream model hosts; review network policy, cache location, and disk usage before use in restricted environments. Long recordings and GPU transcription can consume significant CPU, GPU, memory, and disk cache resources. Require confirmation before transcribing meetings, calls, interviews, voice notes, customer audio, regulated recordings, or files containing other people.
Privacy notes	✓Text, images, and audio passed to Groq tools are sent to Groq's API for inference — do not pass sensitive or personally identifiable data. Your `GROQ_API_KEY` is passed as an environment variable — treat it as a secret and store it securely.	✓Audio content (speech, recordings) is transmitted to Deepgram's servers for transcription and synthesis — review Deepgram's privacy policy for data handling and retention. Your `DEEPGRAM_API_KEY` is passed as an environment variable — treat it as a secret.	✓The MCP client can expose ElevenLabs API keys, voice IDs, text prompts, voice descriptions, uploaded audio samples, generated audio paths, transcripts, diarized speaker labels, and conversational-agent settings. Uploaded audio and generated outputs may contain biometric voice characteristics, names, background sounds, private conversations, or copyrighted material. File, resource, and both output modes can retain generated audio locally, in MCP resources, in logs, or in chat transcripts depending on the client. Treat voice samples and transcripts as sensitive data, and delete generated files or cached resources when they are no longer needed. Review ElevenLabs account, retention, residency, and enterprise data-residency settings before using the server with regulated or customer data.	✓Audio recordings can contain voices, names, accents, speaker identity, background speech, locations, health details, financial details, customer data, credentials spoken aloud, or other sensitive personal information. The upstream MCP example performs local inference and does not require an API key, but MCP clients, model providers, logs, terminal output, transcripts, screenshots, and shared chats can still retain audio paths and transcription text. Generated transcripts, timestamps, and speaker labels may identify individuals or reveal confidential conversations. Model downloads and package installation can contact PyPI, ModelScope, Hugging Face, or other dependency hosts depending on the environment and model configuration.
Prerequisites	A Groq API key (free at console.groq.com). Python with `uv` installed: `pip install uv` or `brew install uv`. An MCP client such as Claude Code or Claude Desktop.	A Deepgram API key (free tier at console.deepgram.com). Python with `pip` available: `pip install deepgram-mcp` to install the package. An MCP client such as Claude Code or Claude Desktop.	Python 3.11 or newer with `uvx` available. An ElevenLabs API key for the account and workspace you intend Claude to use. Review of ElevenLabs pricing, credits, voice-cloning policy, content rules, and data handling before enabling tools that generate or process audio. An approved output directory when using file-based generated audio output.	Python environment with FunASR installed from PyPI or a reviewed source checkout. Local checkout or copy of `examples/mcp_server/funasr_mcp.py` from the FunASR repository. Audio files in an approved location and format such as WAV, MP3, FLAC, M4A, or OGG. Optional GPU, Apple silicon, or CPU device selection through `FUNASR_DEVICE`.
Install	`claude mcp add groq -e GROQ_API_KEY=your-api-key -- uvx groq-mcp`	`claude mcp add deepgram -e DEEPGRAM_API_KEY=your-api-key -- deepgram-mcp`	`uvx elevenlabs-mcp`	`pip install funasr`
Config	`{ "mcpServers": { "groq": { "command": "uvx", "args": ["groq-mcp"], "env": { "GROQ_API_KEY": "your-api-key", "BASE_OUTPUT_PATH": "/path/to/output/directory" } } } }`	`{ "mcpServers": { "deepgram": { "command": "deepgram-mcp", "env": { "DEEPGRAM_API_KEY": "your-api-key" } } } }`	`Manual-only setup: claude mcp add elevenlabs --env ELEVENLABS_API_KEY=YOUR_ELEVENLABS_API_KEY -- uvx elevenlabs-mcp`	`Manual-only setup: pip install funasr`
Citations	Source repositorygithub.com 2026-06-18T07:06:04+00:00 Documentationgithub.com Websiteconsole.groq.com	Source repositorygithub.com 2026-06-18T07:06:04+00:00 Documentationgithub.com	Source repositorygithub.com 2026-06-18T07:06:04+00:00 Documentationraw.githubusercontent.com Submitted by oktofeesh12026-06-06	Source repositorygithub.com 2026-06-18T07:06:04+00:00 Documentationraw.githubusercontent.com Submitted by oktofeesh12026-06-06
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Prerequisites

Schema details

About this resource

Overview

Key capabilities

How it compares

Installation

Claude Code

Claude Desktop

Configuration generation

Requirements

Security

Source Verification Notes

Source citations

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How it compares

Related resources

Deepgram MCP Server for Claude

ElevenLabs MCP Server

FunASR MCP Server

MiniMax MCP Server

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