
mcp playbook
MCP-Playbook: Async RPC the Easy Way Elevator Pitch: MCP-Playbook is your go-to starter kit for quickly building and consuming async RPC tools in Python—no boilerplate fuss, just pure productivity. With both stdio- and SSE-based transports supported out of the box, you’ll be wiring up custom tools and LLM integrations in minutes.
Repository Info
About This Server
MCP-Playbook: Async RPC the Easy Way Elevator Pitch: MCP-Playbook is your go-to starter kit for quickly building and consuming async RPC tools in Python—no boilerplate fuss, just pure productivity. With both stdio- and SSE-based transports supported out of the box, you’ll be wiring up custom tools and LLM integrations in minutes.
Model Context Protocol (MCP) - This server can be integrated with AI applications to provide additional context and capabilities, enabling enhanced AI interactions and functionality.
Documentation
MCP-Playbook: Async RPC the Easy Way
Elevator Pitch:
MCP-Playbook is your go-to starter kit for quickly building and consuming async RPC tools in Python—no boilerplate fuss, just pure productivity. With both stdio- and SSE-based transports supported out of the box, you’ll be wiring up custom tools and LLM integrations in minutes.
🚀 Demonstrated Skills
- Async Programming with
asyncio - RPC Server & Client using
mcpandFastMCP - StdIO & SSE Transports for flexible integration
- Environment Management via
python-dotenv - Dependency Management and virtual environments
- Clean Project Layout and modular code organization
📁 Repository Layout
MCP-Playbook/ ├── .venv/ ← your virtualenv lives here ├── .gitignore ← ignore .venv/, pycache, *.pyc └── mcp-stdio/ ├── client-stdio.py ← Async client that calls your tools ├── server.py ← FastMCP server exposing calculator tool ├── requirements.txt ← Project dependencies └── .env.example ← Sample env vars (if needed)
yaml Copy Edit
🔧 Prerequisites
- Python 3.11+ (3.13 tested)
pipfor installing dependencies- (Optional) A terminal multiplexer or two shells for running client & server side by side
⚙️ Installation
- Clone the repo
git clone https://github.com/your-org/mcp-playbook.git cd mcp-playbook
Create & activate a virtual environment
bash Copy Edit python -m venv .venv
Windows PowerShell
..venv\Scripts\Activate.ps1
Bash / macOS / Linux
source .venv/bin/activate Install dependencies
bash Copy Edit pip install --upgrade pip pip install -r mcp-stdio/requirements.txt 🚦 Usage
- Run the Server Open a terminal in mcp-stdio/ and start the server (stdio transport by default):
bash Copy Edit cd mcp-stdio python server.py You should see:
sql Copy Edit Running server with stdio transport 2. Run the Client In a second terminal (same mcp-stdio/ folder, venv activated):
bash Copy Edit python client-stdio.py Expected output:
sql Copy Edit Available tools:
- add: Add two numbers together 2 + 3 = 5 🔄 Switching to SSE Transport In server.py, change:
python Copy Edit transport = "sse" Restart the server:
bash Copy Edit python server.py Point your HTTP-capable client (or browser) at http://localhost:8050/events
📦 Extending the Playbook Add new tools by decorating functions with @mcp.tool() in server.py.
Customize your client by calling session.call_tool("<your_tool>", arguments={…}).
Integrate LLMs by wiring openai or httpx inside your tool implementations.
🤝 Contributing Fork the repo
Create a feature branch (git checkout -b feature/your-tool)
Commit your changes (git commit -m "Add cool new tool")
Push to your branch (git push origin feature/your-tool)
Open a Pull Request—see our CONTRIBUTING.md for details.
📜 License This project is released under the MIT License. See LICENSE for full details.
Quick Start
Clone the repository
git clone https://github.com/psychoutmedia/mcp-playbookInstall dependencies
cd mcp-playbook
npm installFollow the documentation
Check the repository's README.md file for specific installation and usage instructions.
Repository Details
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