How do I use MCP tools within an agent?

You can use the MCPToolProvider class to register specific servers or individual tools within your agent's tool configuration, allowing the agent to call them during execution.

What is the Model Context Protocol (MCP)?

MCP is an open standard that enables AI models to interact with external tools, APIs, and data sources through a consistent, plug-and-play architecture.

Does it support real-time data updates?

Yes, through MCP Resource Subscriptions, agents can monitor specific data URIs and trigger automated responses when external resources change.

What transport protocols does this skill support?

This skill provides implementation patterns for stdio, HTTP, and SSE (Server-Sent Events) transports, ensuring compatibility with various hosting environments.

Can I secure my MCP server connections?

Yes, the skill includes guidance for implementing API key authentication, restricted permissions, and sandboxing to ensure secure communication between agents and servers.

Microsoft Agent MCP Integration

Name: Microsoft Agent MCP Integration
Author: pagerguild

bypagerguild

API Development

Integrates Model Context Protocol (MCP) servers with the Microsoft Agent Framework to empower AI agents with standardized tool and data access.

About

The ms-mcp skill provides specialized guidance for connecting Microsoft Agent Framework agents to Model Context Protocol (MCP) servers, enabling a standardized bridge between AI models and external environments. This skill simplifies the process of configuring tool providers, managing resources, and implementing various transport protocols like stdio, HTTP, and SSE. It is particularly useful for developers building complex multi-agent workflows in Claude Code that require secure, observable, and high-performance connections to external data sources like GitHub, file systems, or custom internal APIs.

Key Features

Secure resource subscriptions for real-time data monitoring
Standardized tool integration using MCPToolProvider for AI agents
Built-in patterns for authentication, caching, and OpenTelemetry observability
0 GitHub stars
Support for multiple transport layers including stdio, HTTP, and SSE
Dynamic runtime tool loading and MCP server registration

Use Cases

Implementing event-driven agents that respond to live resource updates and subscriptions
Developing custom authenticated MCP servers to bridge proprietary databases with AI workflows
Equipping AI agents with file system and GitHub access via verified MCP servers

About

Key Features

Secure resource subscriptions for real-time data monitoring
Standardized tool integration using MCPToolProvider for AI agents
Built-in patterns for authentication, caching, and OpenTelemetry observability
0 GitHub stars
Support for multiple transport layers including stdio, HTTP, and SSE
Dynamic runtime tool loading and MCP server registration

Use Cases

Implementing event-driven agents that respond to live resource updates and subscriptions
Developing custom authenticated MCP servers to bridge proprietary databases with AI workflows
Equipping AI agents with file system and GitHub access via verified MCP servers