nerding-io/n8n-nodes-mcp

n8n custom node for MCP

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Summary Information

Updated 2 hours ago
Added to GitGenius on September 22nd, 2026
Created on February 14th, 2025
Open Issues & Pull Requests: 76 (+0)
GitHub issues: Enabled
Number of forks: 519
Total Stargazers: 3,040 (+0)
Total Subscribers: 32 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 6.7 hours
Mean response time: 6.2 days
90th percentile: 11.0 days
Tracked items: 77

How this project is maintained

100% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Three people close 53% of everything that gets resolved.

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Issue Activity (beta)

Open issues: 56
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 493 days
Stale 30+ days: 56
Stale 90+ days: 53

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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Detailed Description

n8n-nodes-mcp is a custom node for n8n that enables interaction with Model Context Protocol servers within workflow automation.

The node solves the problem of connecting AI models to external tools and data sources by implementing the Model Context Protocol standard. It allows workflows to connect to MCP servers, access resources, execute tools, and use prompts in a standardized way. The node supports multiple transport methods: command-line based transport using STDIO for local servers, and HTTP Streamable transport as the modern recommended approach for new implementations. Server-Sent Events transport remains available for legacy compatibility but is deprecated.

Teams building AI agent workflows in n8n should adopt this node when they need to integrate external tools and data sources through the MCP standard. It suits projects where AI agents require access to multiple external systems in a standardized protocol. The node requires setting the N8N_COMMUNITY_PACKAGES_ALLOW_TOOL_USAGE environment variable to true when using it as a tool within AI Agents.

The project maintains active engagement with the community through documentation of video tutorials and resources. Development activity shows ongoing refinement of transport mechanisms, with deliberate deprecation of older approaches in favor of modern standards. The maintainers provide security assessment information and actively curate community-contributed learning materials.