MCP Servers
by FrankGenGo
A comprehensive infrastructure for enabling multi-agent AI swarms powered by specialized Model Context Protocol (MCP) servers. This monorepo contains the full stack of components needed to orchestrate, connect, and empower intelligent agents with various specialized capabilities.
Last updated: N/A
What is MCP Servers?
This project enables the creation of a multi-agent AI ecosystem where specialized agents can collaborate, share context, and leverage different capabilities through the Model Context Protocol (MCP). It provides a standardized communication layer for agents to seamlessly access vector databases, specialized tools, and various data sources through a unified protocol.
How to use MCP Servers?
To get started, clone the repository, set up the shared Docker network, start the Qdrant vector database and MCP server, and then start the Inspector dashboard. Access the Inspector dashboard to monitor, test, and debug the MCP servers.
Key features of MCP Servers
Semantic search and retrieval through vector embeddings
Multi-agent collaboration and communication
Modular, microservice-based architecture
Visual inspection and debugging of agent interactions
Use cases of MCP Servers
Multi-Agent Systems: Build collaborative agent systems that combine different AI capabilities
Knowledge Management: Create semantic search systems with intuitive AI interfaces
Tool Integration: Extend AI capabilities with specialized tools and data sources
Development & Debugging: Inspect and test MCP servers during development
FAQ from MCP Servers
What is the Model Context Protocol (MCP)?
What is the Model Context Protocol (MCP)?
MCP is a standardized communication layer that enables agents to seamlessly access vector databases, specialized tools, and various data sources through a unified protocol.
What are the core components of this infrastructure?
What are the core components of this infrastructure?
The core components include the Inspector dashboard, Qdrant-DB with MCP Integration, and the MCP Docker Network.
What are the prerequisites for getting started?
What are the prerequisites for getting started?
The prerequisites include Docker and Docker Compose, Node.js (for local development), and Python 3.9+ (for running clients and scripts).
How do I access the Inspector dashboard?
How do I access the Inspector dashboard?
After starting the Inspector dashboard, you can access it at http://localhost:5173.
Where can I find more resources about MCP?
Where can I find more resources about MCP?
You can find more resources at the Model Context Protocol Specification, MCP Python SDK, MCP TypeScript SDK, and Qdrant Documentation.