mcp-agent is a framework for building AI agents that integrate with Model Context Protocol servers to execute tools and access data. It functions as a multi-agent orchestrator and protocol-compliant server, enabling the creation of agents that can discover and invoke tools from connected external servers.
The project distinguishes itself through a durable workflow engine that supports long-running tasks capable of pausing, resuming, and surviving restarts. It implements complex orchestration patterns, including iterative evaluator-optimizer loops, hierarchical workflow nesting, and specialist request routing to handle multi-step objectives and deep research investigations.
The framework provides comprehensive capabilities for agent management, provider-agnostic model interfaces, and agentic observability using the OTLP standard for distributed tracing and token usage tracking. It also includes systems for secure credential handling via OAuth, cloud deployment for protocol servers, and automated behavior verification for tool execution.
The project includes a command-line interface for project bootstrapping, scaffolding templates, and managing the lifecycle of deployed agent applications.