AGI-MCP-Agent
by ot2net
AGI-MCP-Agent is an open-source intelligent agent framework designed to explore and implement advanced agent capabilities through a Master Control Program (MCP) architecture. It aims to create a flexible, extensible platform for autonomous agents.
Last updated: N/A
What is AGI-MCP-Agent?
AGI-MCP-Agent is an open-source intelligent agent framework that uses a Master Control Program (MCP) architecture to enable advanced agent capabilities. It provides a platform for building autonomous agents that can perform complex tasks, learn from interactions, and coordinate in multi-agent systems.
How to use AGI-MCP-Agent?
To use AGI-MCP-Agent, clone the repository, install the necessary dependencies (using Poetry or pip), set up environment variables (like the OpenAI API key), and run the development server. The project also provides a Makefile with commands for common tasks like formatting, linting, testing, and Docker operations. Docker Compose can be used for quick setup and deployment.
Key features of AGI-MCP-Agent
Master Control Program (MCP) for agent lifecycle management and task scheduling
Agent Framework with cognitive processing, memory management, and tool/API integrations
Environment Interface for standardized interaction with external systems
Multi-Agent Coordination with communication protocols and collaborative problem-solving
Extensible architecture for adding new capabilities and integrations
Use cases of AGI-MCP-Agent
Building autonomous agents for complex problem-solving
Developing multi-agent systems for collaborative tasks
Integrating AI agents with various tools, APIs, and data sources
Experimenting with advanced cognitive models and memory management
FAQ from AGI-MCP-Agent
What is the purpose of the MCP?
What is the purpose of the MCP?
The Master Control Program (MCP) is the central coordination system that manages agent lifecycles, schedules tasks, monitors performance, and orchestrates multi-agent systems.
What are the key components of the Agent Framework?
What are the key components of the Agent Framework?
The Agent Framework includes cognitive processing (planning, reasoning, decision-making), memory management (short-term and long-term), tool/API integrations, perception modules, action generation, and self-monitoring.
How can I contribute to the project?
How can I contribute to the project?
Contributions are welcome! Please check the Contributing Guidelines for details on how to get started.
What technologies are used in the backend?
What technologies are used in the backend?
The backend is built with Python, FastAPI for API interfaces, Pydantic for data validation, SQLAlchemy for database interactions, and LangChain for LLM orchestration.
How do I set up the project locally?
How do I set up the project locally?
You can set up the project locally using Poetry (recommended) or pip. Clone the repository, install dependencies, set up environment variables, and run the development server. Detailed instructions are provided in the README.