MCP Integration

The Model Context Protocol (MCP) is an open standard for connecting AI applications with external data sources and tools. AG-Kit provides comprehensive MCP integration support, enabling you to easily extend your Agent’s capabilities.

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What is MCP?

MCP uses a client-server architecture that allows AI applications to securely access external resources:

• MCP Servers: Provide tools, data sources, and prompt templates
• MCP Clients: AI applications that consume these resources (like AG-Kit Agents)

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Use Cases

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1. Connect to Existing Tool Ecosystems

Many development tools and services already provide MCP servers that you can use directly in AG-Kit:

• Playwright Mcp: Playwright MCP server
• CloudBase AI ToolKit: One-stop backend services for WeChat Mini-Programs and full-stack apps
• Context7: Code documentation for LLMs and AI code editors

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2. Expose AG-Kit Tools

Wrap your AG-Kit tools as MCP servers for use by other AI applications:

• Internal Tool Sharing: Reuse tools across teams
• Cross-Platform Integration: Interoperate with other AI frameworks
• Service Deployment: Provide tools as standalone services

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Quick Start

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Using External MCP Tools

The most common scenario is connecting to existing MCP servers to access their tools:

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Exposing AG-Kit Tools

Expose your AG-Kit tools as an MCP server:

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Connection Types

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Standard Input/Output (Stdio)

The most common connection type, suitable for local tools and command-line programs:

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HTTP Connection

Suitable for remote services and web applications:

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Memory Connection

Used for testing and in-process communication:

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Real-World Examples

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Multi-Server Integration

In real projects, you may need to connect multiple MCP servers to gain different capabilities:

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Error Handling and Monitoring

Production environments require comprehensive error handling and monitoring:

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Next Steps