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MCP Registry: Complete Overview

This document provides a comprehensive, single-file summary of the Infosys Agent Framework (IAF) MCP Integration. It is designed to give any reader a clear understanding of the Model Context Protocol (MCP) system, its architecture, features, API, setup, and configuration.

What is MCP?

The Model Context Protocol (MCP) is a standardized protocol that enables AI agents to securely connect to and interact with external data sources, tools, and services. The IAF MCP Integration extends this protocol for enterprise-grade deployments, supporting robust tool discovery, security, and management.

Key Features

  • Multi-server Support: Connect to multiple MCP servers (local, remote, file-based) simultaneously.
  • Real-time Tool Discovery: Dynamic discovery and validation of tools from running servers.
  • Type Safety: Strict typing and validation for all MCP operations.
  • Enterprise Security: Approval workflows, permissions, and audit trails.
  • Monitoring: Built-in telemetry, performance tracking, and health checks.
  • Multi-tenant Support: Isolated environments for different users.
  • Horizontal Scaling: Designed for high-throughput, scalable environments.
  • Error Recovery: Robust error handling and retry mechanisms.

Architecture Overview

The IAF MCP Integration is built on a modular, layered architecture:

  • Client Layer: Web interface, API clients, and CLI tools for user interaction.
  • API Layer: FastAPI application and routers for handling requests.
  • Service Layer: Services for managing MCP tools, agents, and tags.
  • Repository Layer: Database access and management (PostgreSQL, file system).
  • MCP Runtime Layer: Manages connections to multiple MCP servers and tool execution.

This design ensures secure integration, high availability, and efficient resource utilization.

API Endpoints

The system exposes RESTful API endpoints for managing MCP tools and servers:

  • Add, update, delete, and list MCP tools (local, remote, file-based)
  • Support for file uploads, module references, and URL-based tools
  • Comprehensive OpenAPI documentation
  • Approval workflows and audit logging for all operations

Configuration

  • Environment Variables: Highest priority for configuration.
  • Configuration Files: .env and config.yaml for environment-specific settings.
  • Default Values: Used if no overrides are provided.
  • Database Settings: PostgreSQL connection, pool size, retry logic.
  • Application Settings: App name, version, debug mode, host, and port.

How It All Fits Together

The IAF MCP Integration provides a secure, scalable, and flexible foundation for connecting AI agents to a wide range of external tools and services. Its modular architecture, robust API, and enterprise features make it suitable for production deployments in complex environments. With comprehensive documentation, quick start guides, and detailed configuration options, teams can rapidly onboard, manage, and scale their AI agent integrations.