This project demonstrates integrating MCP tools with Microsoft Semantic Kernel, allowing AI models to interact with external data sources and tools for automation and data retrieval.
Added on:
Created by:
Apr 14 2025
This project demonstrates integrating MCP tools with Microsoft Semantic Kernel, allowing AI models to interact with external data sources and tools for automation and data retrieval.
Added on:
Created by:
Apr 14 2025
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What is Integrate Model Context Protocol (MCP) tools with Semantic Kernel?
This repository provides a comprehensive solution for connecting Model Context Protocol (MCP) servers with Microsoft Semantic Kernel, enabling large language models (LLMs) to call external tools dynamically. It facilitates AI-driven workflows by using MCP as a standardized protocol for tool integration, making AI interactions more contextual and versatile. The system supports connecting to MCP servers, converting tools into Semantic Kernel functions, and orchestrating complex workflows within the .NET environment. It is ideal for developers aiming to enhance AI capabilities with external data sources like APIs, databases, or services for automation, data retrieval, and system integration.
Who will use Integrate Model Context Protocol (MCP) tools with Semantic Kernel?
- AI developers
- Software engineers
- Researchers working on AI orchestration
- Automation professionals
- Developers building intelligent workflows
How to use the Integrate Model Context Protocol (MCP) tools with Semantic Kernel?
- Step 1: Clone the repository from GitHub.
- Step 2: Restore dependencies using 'dotnet restore'.
- Step 3: Configure your LLM API key via environment variables or secrets.
- Step 4: Connect to an MCP server using the provided C# code snippet.
- Step 5: List available tools from the MCP server and integrate them into Semantic Kernel workflows.
- Step 6: Develop custom workflows or applications using the integrated tools.
Integrate Model Context Protocol (MCP) tools with Semantic Kernel's Core Features & Benefits
The Core Features
- Connect to MCP server
- List tools available on MCP
- Call external tools via Semantic Kernel
- Build AI-driven workflows
The Benefits
- Enables seamless interaction between LLMs and external tools
- Standardizes tool integration with MCP protocol
- Supports dynamic function calling in AI workflows
- Enhances AI interoperability and contextual understanding
Integrate Model Context Protocol (MCP) tools with Semantic Kernel's Main Use Cases & Applications
- AI automation in enterprise systems
- Data retrieval from external APIs and databases
- Orchestration of complex AI workflows
- AI-driven system integrations
FAQs of Integrate Model Context Protocol (MCP) tools with Semantic Kernel
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