Summary
GroqCloud with your own API key: fast chat completions from open models such as Llama, GPT-OSS and Qwen, speech-to-text and translation into English of audio files from a public link with Whisper, and the models, batch jobs and files of the organization.
Guided setup
Connect Groq to Microsoft Copilot in 2 minutes
Start a free trial on AnythingMCP Cloud, connect Groq in the guided setup, then add your MCP URL to Microsoft Copilot. No code and no server to run.
No credit card · 7-day trial · Self-host alternative available
Try asking
Example prompts for Groq
Click any prompt to copy it. Paste into Claude, ChatGPT, Cursor, Gemini, Copilot or OpenClaw to run it against this connector.
Claude is AI and can make mistakes. Please double-check responses.
💡 No install? Use cloud.anythingmcp.com directly. Sign in, click Connectors → Groq, paste your credentials, mint an MCP API key and you're done. No Docker, no
git clone, no local server.
Groq + Microsoft Copilot
GroqCloud with your own API key: fast chat completions from open models such as Llama, GPT-OSS and Qwen, speech-to-text and translation into English of audio files from a public link with Whisper, and the models, batch jobs and files of the organization.
Prerequisites
See the full setup instructions baked into the connector (visible in the in-app store when you select the connector). The required environment variables for this connector are:
GROQ_API_KEY
Step 1 — Get credentials
Setting up takes about 2 minutes. You need a GroqCloud account; the free plan works within its rate limits.
- Sign in at https://console.groq.com and open API Keys (https://console.groq.com/keys).
- Click Create API Key, give it a name and copy it. It starts with
gsk_and Groq shows it only once. - Paste it into
GROQ_API_KEY, without the wordBearer. The connector sends it asAuthorization: Bearerand only to Groq. - Install the connector and run
groq_list_models: it lists the models the key can use and confirms the key.
Which tools cost money: groq_chat_completion, groq_transcribe_audio and groq_translate_audio run a model. On the free plan they are free but rate limited; on the Developer plan every call is billed to the organization: text per input and output token, Whisper per hour of audio with a minimum of 10 seconds per request. The AI asks you before large or repeated calls and sets max_completion_tokens to cap a reply. groq_list_models, groq_get_model, groq_list_batches, groq_get_batch, groq_list_files and groq_get_file cost nothing.
Models: groq_list_models shows every model the key can use with owner, context_window, max_completion_tokens and whether it is active; groq_get_model reads one and answers 404 for a model the key cannot use. Model ids change often: preview models can be removed at short notice, production models are stable. Common ids are llama-3.3-70b-versatile, llama-3.1-8b-instant (the cheapest), openai/gpt-oss-120b, openai/gpt-oss-20b and qwen/qwen3.8-27b; for audio whisper-large-v3-turbo (cheaper) and whisper-large-v3.
Text: groq_chat_completion takes model and messages and returns the whole reply at once (no streaming). response_format asks for JSON or a JSON schema, tools adds function calling, and reasoning_effort and reasoning_format steer reasoning models (GPT-OSS takes low, medium or high; Qwen takes none or default).
Audio: groq_transcribe_audio writes speech down in its own language, groq_translate_audio turns it into English text (only whisper-large-v3 translates). Both take a public link in url: Groq downloads the file itself, so nothing is uploaded. Formats: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, webm. Passing language (ISO-639-1, for example de) makes it faster and more accurate. response_format verbose_json adds segments with timestamps, timestamp_granularities word adds word timings.
Batch jobs and files: groq_list_batches and groq_get_batch show batches started elsewhere with their status (validating, in_progress, finalizing, completed, failed, expired, cancelling, cancelled), request counts and the output_file_id and error_file_id. groq_list_files and groq_get_file show file name, size in bytes, purpose (batch or batch_output) and creation time, not the content.
Data formats: a completion returns choices[0].message.content, finish_reason (stop, length when max_completion_tokens was reached, tool_calls) and usage with token counts and timings in seconds; reasoning models may put their reasoning in choices[0].message.reasoning. The result also carries _headers with the requests and tokens left in the rate limit. A transcription returns text. Timestamps such as created are Unix seconds, UTC.
Paging: the list tools have no paging parameters; they return what Groq sends in one answer.
Switched off at install: nothing. All 9 tools are on, and none of them deletes anything.
Limits: rate limits apply per organization and model, as requests and tokens per minute and per day (https://console.groq.com/settings/limits). Audio links may point to files of up to 25 MB on the free plan and 100 MB on paid plans.
Common errors: 400 means a parameter the model does not support or audio that cannot be read; 401 a wrong or deleted key; 403 the project may not use this model; 404 an unknown model, batch or file; 413 an audio file that is too large; 429 the rate limit is reached (the AI waits the seconds in retry-after instead of retrying in a loop); 498 the flex tier is out of capacity; 500 and 503 are Groq problems, retry once later.
The connector does not stream replies, does not upload or download file content, and does not create or cancel batch jobs.
Step 2 — Install the adapter
curl -fsSL https://raw.githubusercontent.com/HelpCode-ai/anythingmcp/main/docker-compose.quickstart.yml -o docker-compose.yml
printf 'JWT_SECRET=%s\nENCRYPTION_KEY=%s\n' "$(openssl rand -hex 32)" "$(openssl rand -hex 32)" > .env
docker compose up -d
Step 3 — Add the connector in Microsoft Copilot
Your server URL: in AnythingMCP, open MCP Servers → the server this connector is on, and copy its URL (
https://cloud.anythingmcp.com/mcp/…). Use it wherever this guide showsYOUR_SERVER_ID.
Microsoft Copilot uses MCP servers through agents built in Copilot Studio: you add AnythingMCP to an agent as a tool, then publish the agent to Microsoft 365 Copilot and Teams. Copilot Studio connects from Microsoft's cloud over Streamable HTTP, which AnythingMCP supports.
- In Copilot Studio, open your agent (or create one), go to Tools and choose Add a tool → New tool → Model Context Protocol.
- Enter a Server name (for example
AnythingMCP), a Server description that says what the connector does, and the Server URLhttps://cloud.anythingmcp.com/mcp/YOUR_SERVER_ID. Copilot Studio uses the description to decide when to call the server. - Under authentication, choose API key, set Type to Header and the header name to
X-API-Key, then select Create. - In Add tool, choose Create a new connection, paste an MCP API key from AnythingMCP (MCP Servers → your server → API keys) and select Add to agent.
- Try it in the agent's Test pane: ask for something that needs the
Groqtools. - Select Publish, then Channels → Microsoft 365 and Microsoft Teams, keep Make agent available in Microsoft Copilot selected and choose Add channel. See agent in Teams installs it for you; in Microsoft 365 Copilot, type @ and pick the agent.
Prefer per-user sign-in? Choose OAuth 2.0 → Dynamic discovery instead of an API key: each user then signs in to AnythingMCP the first time the agent calls it.
Self-hosting? Use your instance's public HTTPS address instead of https://cloud.anythingmcp.com. Copilot Studio connects from Microsoft's cloud, so localhost does not work.
Available tools
| Tool | What it does |
|---|---|
groq_list_models | List the models this Groq API key can use (chat, reasoning, Whisper speech-to-text, text-to-speech, safety), with owner, context window… |
groq_get_model | Read one Groq model: owner, creation time, context window, maximum completion tokens and whether it is active |
groq_chat_completion | Send a conversation to a Groq-hosted model and return its reply (non-streaming) |
groq_transcribe_audio | Transcribe speech in an audio file to text in its own language with Whisper |
groq_translate_audio | Translate speech in an audio file into English text with Whisper (only whisper-large-v3 translates) |
groq_list_batches | List the Batch API jobs of the Groq organization: endpoint, status (validating, in_progress, finalizing, completed, failed, expired… |
groq_get_batch | Read one Groq batch job: status, timestamps of each stage, request counts (total, completed, failed), errors, metadata and the… |
groq_list_files | List the files stored in the Groq organization (batch inputs and batch outputs) with id, file name, size in bytes, purpose and creation time |
groq_get_file | Read the metadata of one Groq file: name, size in bytes, purpose (batch or batch_output) and creation time |
Example prompts
- "Which Groq models can my key use right now, and what is the context window of each?"
- "Summarize this support email in three bullet points with llama-3.1-8b-instant and keep the reply under 200 tokens."
- "Transcribe the German podcast episode at https://example.com/audio/episode-12.mp3 with timestamps per segment."
- "Translate the Italian voice message at https://example.com/voice/note.m4a into English text."
- "Show me the status of my Groq batch jobs and how many requests failed in the last one."
FAQ
Which Copilot is this for? Microsoft 365 Copilot at work, through agents built in Copilot Studio. The Microsoft Copilot app for personal accounts has no option to add your own MCP server.
What do I need? A work account with access to Copilot Studio (a license or a trial) to build the agent. People who use it in Microsoft 365 Copilot or Teams need access to the agent: share it with them, or ask an admin to publish it to the organization. If your organization applies data policies to Power Platform connectors, they cover MCP servers too.
The agent doesn't call the tools. Check that the header name is exactly X-API-Key and that the key belongs to the same MCP server as the URL, and make the server description specific: Copilot Studio uses it to decide when to call the server. Publish the agent again after each change; in an open chat, type "start over" to get the new version.
Next steps
- Connector landing page
- Connect to Claude
- Connect to ChatGPT
- Connect to Cursor
- Connect to Gemini
- Connect to Meta Muse
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