MCP server with AI agent as a tool context reducer
Needs changesWhat 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 OpenAI Chat Model and MCP Client.
How it runs
Trigger: When an MCP client calls one of its tools (plus 1 other trigger).
- Set Github Username (Edit Fields (Set)): sets 1 field: githubUsername
- Github AI Agent (AI Agent): runs an AI agent, with model: OpenAI Chat Model; 1 tool (Github API); memory: Simple Memory
Services it uses
Before you upgrade to n8n 3.0
1 thing in this workflow is removed in n8n 3.0. Fix it before you upgrade:
- AI Agent v1 (old agent modes) in Github AI Agent (v1.9): replace with Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent.
Rather not rewrite it? Many of these flows can be rebuilt in Make (free plan).
| Removed in 3.0 | Replace with |
|---|---|
| AI Agent v1 (old agent modes) Github AI Agent (v1.9) | Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent. |
Nodes used (8)
- MCP Server Trigger
@n8n/n8n-nodes-langchain.mcpTrigger - Execute Workflow Trigger
n8n-nodes-base.executeWorkflowTrigger - Simple Memory
@n8n/n8n-nodes-langchain.memoryBufferWindow - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - Call n8n Workflow Tool
@n8n/n8n-nodes-langchain.toolWorkflow - MCP Client Tool
@n8n/n8n-nodes-langchain.mcpClientTool - AI Agent
@n8n/n8n-nodes-langchain.agent - Edit Fields (Set)
n8n-nodes-base.set
From the author
Overview Transform your LLM into a powerful GitHub automation specialist with this n8n workflow template. In a world where multiple MCP servers can overwhelm LLMs with context, this streamlined solution provides a dedicated GitHub Agent that handles all…