This MCP server facilitates integration between Microsoft Copilot Studio agents and MCP-compatible clients, supporting conversation context, structured responses, and configurable agent definitions. It leverages DirectLine API for communication, maintaining session continuity and structured data exchange, making it suitable for deploying intelligent Copilot agents in various environments.
Added on:
Created by:
Apr 28 2025
This MCP server facilitates integration between Microsoft Copilot Studio agents and MCP-compatible clients, supporting conversation context, structured responses, and configurable agent definitions. It leverages DirectLine API for communication, maintaining session continuity and structured data exchange, making it suitable for deploying intelligent Copilot agents in various environments.
Added on:
Created by:
Apr 28 2025
Aakash - The Sky
Featured
What is MCP server for Copilot Studio Agents?
The MCP server for Copilot Studio Agents acts as a bridge enabling MCP-compatible clients to connect with Microsoft Copilot Studio agents through a robust API. It supports features like stateful conversations, context preservation across multiple queries, and structured responses, facilitating seamless integration. Users can configure their agents, set environment variables for security, and interact via various methods such as direct API calls or Docker containers. The server offers tools for querying agents, maintaining conversational history, and ensuring data security. Its modular setup allows developers to extend functionality, making it ideal for deploying AI assistants, automating workflows, and enhancing enterprise productivity using Copilot Studio agents within an MCP framework.
Who will use MCP server for Copilot Studio Agents?
- Developers integrating Copilot Studio agents
- Organizations deploying AI assistants
- Enterprise users automating workflows
- AI and ML researchers
- System integrators
How to use the MCP server for Copilot Studio Agents?
- Step1: Set up and configure your Copilot Studio agent, including security and environment variables.
- Step2: Update `agent_definitions` in the main.py with your agent’s details.
- Step3: Install dependencies using Python or Docker as per your environment.
- Step4: Run the server using `mcp run` command, configuring environment variables for endpoint and secret.
- Step5: Connect your MCP-compatible client to the server URL and start sending queries.
- Step6: Use conversation IDs and watermarks to maintain context across sessions.
MCP server for Copilot Studio Agents's Core Features & Benefits
The Core Features
- Connects to Copilot Studio agents via DirectLine API
- Maintains conversation context
- Supports stateful interactions with conversation ID and watermarks
- Configurable agent definitions
- Structured response handling
The Benefits
- Seamless integration with Microsoft Copilot Studio
- Supports persistent contextual conversations
- Flexible setup for various deployment environments
- Enhanced automation and AI-powered workflows
- Secure and customizable agent interactions
MCP server for Copilot Studio Agents's Main Use Cases & Applications
- Enterprise AI assistant deployment
- Automated customer support with AI agents
- Workflow automation integrating Copilot agents
- Research and development of conversational AI
- Custom automation solutions for businesses
FAQs of MCP server for Copilot Studio Agents
Developer
- CrewAakash
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