AI Agents Lab
Provides a suite of AI agent architectures built on the Model Context Protocol (MCP) for standardized, context-aware AI systems.
About
The AI Agents Lab is a comprehensive suite of projects designed to explore, implement, and document AI agent architectures powered by the Model Context Protocol (MCP). This repository serves as a central hub for cutting-edge MCP-based agent systems, providing full documentation, protocol guides, and open-source tools to facilitate the development of modular, interoperable AI agents. The lab includes tools for context injection, message formatting, dataset conversion, context chaining, and a proxy layer for connecting agents with external resources, along with reference AI agents that demonstrate MCP's capabilities.
Key Features
- Dataset Tools for converting data into MCP-compliant datasets
- MCP Agent Framework for building modular agents
- MCP Message Handler for context injection and formatting
- MCP Proxy Layer for connecting agents to external resources
- Context Chain Builder for automating complex tasks
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Use Cases
- Building task executors that operate within a defined context
- Developing planning agents that leverage chained MCP messages for complex problem-solving
- Creating summarization agents for context-aware information distillation
