Overview
The MCP (Model Context Protocol) Node enables AI agents to use tools from MCP servers. This node enables you to:- Connect to MCP-compliant tool servers
- Use external tools and APIs through standardized interfaces
- Extend AI capabilities with specialized functions
- Integrate with services that provide MCP servers
- Access resources and tools from various providers
Configuration Parameters
Node Configuration
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MCP Server:
Select which MCP server to connect to. Available options include:
- GitHub MCP Server (for GitHub operations)
- Other configured MCP servers
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Query:
The task or question for the agent to accomplish using the MCP server’s tools
What tools can you use?
Create a new issue in the repository
Search for pull requests related to bug fixes
Advanced Settings
Advanced Settings
- System Prompt: Customize how the agent uses MCP tools
- Model: Select the language model (must support function calling)
- Max Steps: Maximum number of reasoning and tool-use iterations (1-50)
Expected Inputs and Outputs
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Inputs:
- The node accepts text input that can be referenced in the query
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Outputs:
- output: The agent’s final response after using MCP tools
- conversation: Detailed log of tool calls and reasoning
Use Case Examples
- GitHub Automation: Use the GitHub MCP server to automate repository operations like creating issues, managing pull requests, or updating code.
- External Service Integration: Connect to MCP servers provided by third-party services for specialized functionality.
- Tool Discovery: Query MCP servers to discover available tools and capabilities, then use them dynamically.
Error Handling and Troubleshooting
- MCP Server Connection: Ensure the MCP server is accessible and properly configured with any required authentication.
- Tool Compatibility: Not all MCP tools may work as expected. This is an experimental feature with ongoing improvements.
- Model Selection: Use models with strong function-calling capabilities for reliable MCP tool usage.