mcp-agent allows building effective AI agents with MCP servers using simple, composable patterns for enhanced agent functionality.
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Aggregates multiple MCP servers into a single unified interface, reducing system resource usage and simplifying configuration management with dynamic reloading and tag-based filtering capabilities. Highly relevant as a tool for managing and orchestrating MCP servers.
Server enabling the batching of multiple MCP tool calls into a single request, reducing token usage and network overhead for AI agents.
Integrates Dify's AI application development platform with MCP-compatible tools and services, enabling seamless extension of Dify applications while maintaining MCP server compatibility.
Ectors is an actor-based MCP (Model Context Protocol) server that manages multiple routers with unique IDs. It supports various transport protocols for modular and composable MCP service delivery, making it a flexible solution for building and scaling MCP server infrastructures.
An MCP server extension for the Eunomia framework, connecting Eunomia instruments with MCP servers to orchestrate data governance and access policies.
Foxy Contexts enables declarative MCP server development in Golang, with built-in functional testing to ensure reliable Model Context Protocol implementation.
Source: https://github.com/lastmile-ai/mcp-agent
Category: mcp-middleware-orchestration
Tags: ai-agent, middleware, mcp, open-source
mcp-agent is an open-source, Python-based framework for building effective AI agents using the Model Context Protocol (MCP). It provides simple, composable patterns for constructing robust, production-ready agent applications that can interact with various MCP servers and expose their tools to large language models (LLMs).
mcp-agent is open source and free to use under the Apache-2.0 license.
Note: mcp-agent is under active development and welcomes contributions from the community.