Documentation Lookup AI Agent using Context7 and Gemini
UnknownUnknown. This template uses community nodes we can't verify statically. Uses community nodes that can't be verified statically (unverified community packages are off by default in 3.0). Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 8 nodes and runs when an MCP client calls one of its tools (plus 1 other trigger). Along the way it connects Google Gemini Chat Model and Mcp (community).
How it runs
Trigger: When an MCP client calls one of its tools (plus 1 other trigger).
- Context7 AI Agent (AI Agent): runs an AI agent, with model: Google Gemini Chat Model; 2 tools (context7-get-library-docs, context7-resolve-library-id); memory: Simple Memory
Services it uses
Before you upgrade to n8n 3.0
We can't fully verify this one: it relies on 1 community package, and n8n 3.0 turns unverified community packages off by default (N8N_UNVERIFIED_PACKAGES_ENABLED=false).
- Check that n8n-nodes-mcp is verified or supports 3.0 (used in context7-resolve-library-id, context7-get-library-docs).
Nodes used (7)
- Google Gemini Chat Model
@n8n/n8n-nodes-langchain.lmChatGoogleGemini - Mcp Client Tool
n8n-nodes-mcp.mcpClientTool - MCP Server Trigger
@n8n/n8n-nodes-langchain.mcpTrigger - AI Agent
@n8n/n8n-nodes-langchain.agent - Execute Workflow Trigger
n8n-nodes-base.executeWorkflowTrigger - Simple Memory
@n8n/n8n-nodes-langchain.memoryBufferWindow - Call n8n Workflow Tool
@n8n/n8n-nodes-langchain.toolWorkflow
From the author
This n8n workflow template uses community nodes and is only compatible with the self-hosted version of n8n. This workflow demonstrates how to build and expose a sophisticated n8n AI Agent as a single, callable tool using the Multi-Agent Collaboration Protocol…