MCP
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCPList the available MCP tools and give me an example of how I could use one."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
python3 -m venv .venv or python -m venv .venv source .venv/bin/activate pip install --upgrade pip pip install -r requirements.txt .venv\Scripts\python.exe app.py
Local MCP + Groq + OpenAI Agents SDK
This classroom example contains:
app.py: a persistent local Streamable HTTP MCP server with several tools.mcp_groq_agent.ipynb: an agent that discovers and calls those tools.
Setup
Use Python 3.10 or newer. In a terminal, enter this project folder, create a
virtual environment, and install everything needed by both the server and notebook
(replace python3.11 with your modern Python command if necessary):
cd /Users/somenathmandal/Documents/transfer/grok-playground/MCP
python3.11 -m venv .venv
source .venv/bin/activate
python -m pip install -r requirements.txtCreate .env from the example and put your Groq API key in it:
cp .env.example .envGROQ_API_KEY=replace_with_your_groq_key
GROQ_MODEL=openai/gpt-oss-20bNever commit or share .env; it is excluded by .gitignore.
Related MCP server: Enterprise MCP Gateway and Tool Registry
Run the MCP server
Start the MCP server in one terminal and leave it running:
source .venv/bin/activate
.venv/bin/python app.pyThe Streamable HTTP endpoint is now available at:
http://127.0.0.1:8000/mcpKeep that terminal open. Press Ctrl+C when you want to stop the server.
Run the agent notebook
In a second terminal:
cd /Users/somenathmandal/Documents/transfer/grok-playground/MCP
source .venv/bin/activate
jupyter lab mcp_groq_agent.ipynbSelect the .venv Python kernel if Jupyter asks, then run the cells from top to
bottom. The notebook connects directly to http://127.0.0.1:8000/mcp; it never
starts or imports app.py. The Groq API key is loaded from .env and is never
stored in the notebook.
How the pieces connect
Notebook agent
-> Groq OpenAI-compatible API (model reasoning and tool selection)
-> http://127.0.0.1:8000/mcp (tool discovery and execution)
-> app.py MCP toolsThe server must be running before executing the MCP connection cells. If the
notebook reports a connection error, first confirm that the server terminal says
Uvicorn is running on http://127.0.0.1:8000.
The notebook also guards against stale certificate-file environment variables occasionally inherited from notebook launchers. It removes a certificate variable only when the referenced path does not exist; valid custom certificate settings are preserved.
MCP
This server cannot be deployed
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