MCP100 IndexAI & Reasoning

ShortlistFirst-party MCP

groq

by ecosystem:groq

Updated September 21, 2026

AI & ReasoningSoftware & TechnologyAccess · Self-hosted

MCP100 verdict

Connect compatible AI clients to the capabilities exposed by Groq's current MCP server and related developer workflows.

MCP100 Assessment

Editorial verdict

Promising first-party tooling, but it remains on the Shortlist until the current distribution, concrete tool surface, permission model, data handling, and independent usability are more completely reviewed.

Reviewed July 30, 2026

Task Fit

Mapped

Specialized workflows

Trust

Status warning

mcp_relevance; documentation; client_coverage; tool_contract; install_supply_chain; advisory_freshness; resource_type_requirements

Maintenance

Activity observed

A dated repository or package update is available; editorial maintenance review is still pending.

Popularity

Signals available

Visible usage signals are shown for discovery only, not as proof of safety.

Best for

Low-latency model-inference and multimodal processing workflows.

Not ideal for

Production use before the documented maturity gaps are resolved

Avoid if

The connected identity is broader than the task requires
Tool calls cannot be reviewed before consequential mutations

Trade-offs

The implementation has limited maintenance history and a narrower evidence base than established Recommended entries.

Evidence scope

Evidence

Current source snapshot

Popularity

43 MCP repository stars

Repository-distributed · no current public package metric

Repository identity: groq/groq-mcp-server

Official Groq MCP repository is public. Its repository-local groq-mcp project identity is not currently available on PyPI, so no package download metric is shown.

Stars observed August 14, 2026 · Downloads observed September 8, 2026

Exact implementation repository metric.

Official Groq MCP repository is public. Its repository-local groq-mcp project identity is not currently available on PyPI, so no package download metric is shown.

Maintenance

Publisher activity observed August 13, 2026

Current source snapshot

Trust review

Source relationship: First-party MCP

Reviewed July 30, 2026

Sources

GitHub repository ↗

Evidence-backed setup

Install & Agents

Choose your MCP client. A client connects to the MCP server; the language model is selected inside that client. Only stored, source-backed configurations are shown.

Claude Code

Local stdio

MCP100 logic checked

claude mcp add groq -e GROQ_API_KEY="YOUR_GROQ_API_KEY" -e BASE_OUTPUT_PATH="/absolute/path/to/groq-output" -- uvx "groq-mcp"

The publisher connection details were combined with this client's official MCP transport configuration; installation was not executed by MCP100.

Verify safely: Restart Claude Code, confirm groq tools are listed, and perform one read-only test with non-sensitive data.

Uninstall and revoke

Remove groq from Claude Code, restart the client, remove any separately installed package, and revoke dedicated credentials if used.

Evidence & methodology

Publisher-documented setup is not the same as MCP100 execution testing. “MCP100 logic checked” means the stored configuration shape was reviewed, not that third-party MCP software was run.

Evidence checked 2026-08-12

Evidence 1 ↗Evidence 2 ↗

Read additional publisher installation details

From the publisher README

Publisher installation details

Original client setup and configuration retained from the publisher documentation.

View original README ↗

Publisher-documented clients

Claude Desktop

These names appear in the publisher's installation documentation. MCP100-verified configurations are shown separately above when available.

Quickstart with Claude Desktop

Get a Groq API key for free at console.groq.com

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.
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".

Installation Options

Option 1: Quick Setup (Recommended)

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
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

Option 2: Manual Setup

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

Loading optional publisher installation details…

Read publisher documentation

Publisher documentation

Publisher README

Original product, capability, tool, and usage documentation from the MCP publisher. Installation sections appear under Install & Agents.

View original README ↗

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)

Other MCP Clients

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

Contributing

If you want to contribute or run from source:

Available Scripts

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

Vision & Image Analysis

./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?"

Text-to-Speech (TTS)

./scripts/groq_tts.sh "Your text" [voice_name] [model] [output_directory]
# Example:
./scripts/groq_tts.sh "Hello, world!" "Arista-PlayAI"

Speech-to-Text (STT)

./scripts/groq_stt.sh <audio_file> [model] [output_directory]

Utility Scripts

list_groq_voices.sh: Display available TTS voices
list_groq_stt_models.sh: Show available STT models
groq_batch.sh: Process batch operations
groq_translate.sh: Translate text or audio

Development Scripts

# 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

Troubleshooting

Logs when running with Claude Desktop can be found at:

Windows: %APPDATA%\Claude\logs\groq-mcp.log
macOS: ~/Library/Logs/Claude/groq-mcp.log

Acknowledgments

This project is inspired by the ElevenLabs MCP Server. Thanks!

Loading optional publisher documentation…

FAQ

What can Groq MCP do?

Use Groq inference and multimodal workflows through an official MCP server.

Can Groq MCP generate speech, transcribe audio, analyze images, and run chat completions?

The reviewed tool surface includes text_to_speech, transcribe_audio, analyze_image, and chat_completion. This does not claim that MCP100 executed those tools.

Does Groq MCP work with Codex?

Yes. MCP100 reviewed an evidence-backed setup for Codex, but has not independently verified it with a live runtime test.

Does Groq MCP require an API key?

The official server uses a Groq API key.

What are the main production risks of Groq MCP?

The implementation has limited maintenance history and a narrower evidence base than established Recommended entries. Use a test environment where practical, least-privilege credentials, narrowly enabled tools, and explicit confirmation for mutations. MCP100 did not execute third-party server code during this documentation review.

Is this an official MCP?

ecosystem:groq is listed as First-party MCP in MCP100’s current evidence.

Current official resources:

Publisher documentation ↗

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).

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)

Other MCP Clients

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

Contributing

If you want to contribute or run from source:

Available Scripts

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

Vision & Image Analysis

./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?"

Text-to-Speech (TTS)

./scripts/groq_tts.sh "Your text" [voice_name] [model] [output_directory]
# Example:
./scripts/groq_tts.sh "Hello, world!" "Arista-PlayAI"

Speech-to-Text (STT)

./scripts/groq_stt.sh <audio_file> [model] [output_directory]

Utility Scripts

list_groq_voices.sh: Display available TTS voices
list_groq_stt_models.sh: Show available STT models
groq_batch.sh: Process batch operations
groq_translate.sh: Translate text or audio

Development Scripts

# 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

Troubleshooting

Logs when running with Claude Desktop can be found at:

Windows: %APPDATA%\Claude\logs\groq-mcp.log
macOS: ~/Library/Logs/Claude/groq-mcp.log

Acknowledgments

This project is inspired by the ElevenLabs MCP Server. Thanks!

Promising first-party tooling, but it remains on the Shortlist until the current distribution, concrete tool surface, permission model, data handling, and independent usability are more completely reviewed.

Best for

Not ideal for

Avoid if

Trade-offs

Evidence

Popularity

Maintenance

Trust review

Sources

Install & Agents

Claude Code

Publisher installation details

Quickstart with Claude Desktop

Installation Options

Option 1: Quick Setup (Recommended)

Option 2: Manual Setup

What it does

Representative uses

Important limits

Context Footprint

Access & risk

Other options

Chrome DevTools MCP

Sequential Thinking MCP

JADX-AI-MCP (Part of Zin MCP Suite)

Publisher README

Groq MCP Server

Agentic Tasks, Code Generation & Web Search

Vision & Understanding

Speech & Audio

Batch Processing

Other MCP Clients

Contributing

Available Scripts

Vision & Image Analysis

Text-to-Speech (TTS)

Speech-to-Text (STT)

Utility Scripts

Development Scripts

Troubleshooting

Acknowledgments

FAQ

Publisher installation details

Quickstart with Claude Desktop

Installation Options

Option 1: Quick Setup (Recommended)

Option 2: Manual Setup

Publisher README

Groq MCP Server

Agentic Tasks, Code Generation & Web Search

Vision & Understanding

Speech & Audio

Batch Processing

Other MCP Clients

Contributing

Available Scripts

Vision & Image Analysis

Text-to-Speech (TTS)

Speech-to-Text (STT)

Utility Scripts

Development Scripts

Troubleshooting

Acknowledgments