Mcp Ai Lab

MCP AI Agents LAB 🤖📚

Model Context Protocol (MCP) + AI Agents: A suite of advanced projects that explore, implement, and document AI agent architectures powered by standardized context protocols.

This repository serves as a unified hub for cutting-edge MCP-based agent systems, with full documentation, protocol guides, and open-source tools.

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🚀 Projects in this Suite

• 🧠 MCP Agent Framework: Build modular, interoperable AI agents that communicate via Model Context Protocol.
• 🔄 MCP Message Handler: Universal handler for context injection and protocol message formatting.
• 📦 Dataset Tools: Tools to convert real-world context data into MCP-compliant datasets.
• 📝 Context Chain Builder: Automate the chaining of multiple MCP messages to simulate complex tasks.
• 🌐 MCP Proxy Layer: Middleware to connect MCP agents with APIs, databases, and models (LLMs, RAG systems).
• 🤖 Example Agents: Reference AI agents (task executors, summarizers, planners) built fully on MCP.

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📚 Documentation

Explore full guides and technical breakdowns:

• [🌐 What is Model Context Protocol?](docs/WHATISMCP.md)
• [🛠️ Building an MCP Agent](docs/BUILD_AGENT.md)
• [📦 MCP Message Format Spec](docs/MESSAGE_FORMAT.md)
• [🔗 Chaining MCP Contexts](docs/CHAINING.md)
• [🧑‍💻 Running Example Agents](docs/RUN_EXAMPLES.md)

📖 Start here: [Getting Started Guide](docs/GETTING_STARTED.md)

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🌐 Useful External Links

• 📄 MCP Official Spec: https://modelcontext.org/spec
• 💬 MCP Community Forum: https://community.modelcontext.org
• 🔗 LangChain MCP Integration: https://github.com/langchain-ai/langchain
• 🧩 OpenAI MCP Resources: https://platform.openai.com/docs

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🔧 Requirements

• Python 3.10+
• pydantic, requests, fastapi (for protocol servers)
• Optional: torch, transformers (for LLM-backed agents)

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🏃‍♂️ Quick Start

# Clone the repo
git clone https://github.com/yourusername/mcp_ai_lab.git
cd mcp_ai_lab

# Install requirements
pip install -r requirements.txt

# Run an example agent
python agents/example_agent.py

## Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [techySPHINX](https://github.com/techySPHINX)
- **Source:** [techySPHINX/mcp_ai_lab](https://github.com/techySPHINX/mcp_ai_lab)
- **License:** MIT

Install and usage instructions live in the source repository linked above.