"MCP-N8N integration or server" matching MCP servers:

A Model Context Protocol server that provides AI assistants with comprehensive access to n8n node documentation, properties, and operations for effective workflow automation.

A TypeScript-based server to interact with ArangoDB using the Model Context Protocol, enabling database operations and integration with tools like Claude and VSCode extensions for streamlined data management.

A Model Context Protocol server that allows AI assistants to save structured information to n8n via webhooks for storage, indexing, and retrieval.

MCP for Azure DevOps Boards is a MCP server that lets your favourite AI browse, query and update Azure DevOps work items as if it were a project manager. Written in Rust and optimized for tokens usagem, It runs via stdio or HTTP mode and uses standard Azure authentication with az login.

A proof of concept MCP server for Apache OFBiz

The Wanaku MCP Router stands between autonomous AI agents and your enterprise systems. Wanaku leverages proven integration technology, like Apache Camel, to set up and manage hundreds or thousands of integrations.

Enables chat with multiple LLM providers (OpenAI and Anthropic) while maintaining persistent conversation memory. Provides extensible tool framework for various operations including echo functionality and conversation storage/retrieval.

Wraps n8n with an MCP server and vector storage to enable semantic search, management, and execution of automated workflows. It integrates with other tools to make workflows searchable and orchestratable within a larger automation ecosystem.

he Maximo MCP Server bridges AI agents (Claude, Cursor, Antigravity) with your IBM Maximo environment. It empowers your AI to autonomously discover Object Structures (APIs), inspect schemas, and query live data via OSLC. Instead of hallucinating field names, the AI validates queries instantly and ca

Enables storing, semantically searching, listing, and deleting text records in any Qdrant collection using plain vectors compatible with default LangChain and n8n setups.

A FastMCP-based MCP server for the R2R API, enabling integration with document management, knowledge graphs, and RAG systems through automatically generated tools and resources.

Provides read-only MCP tools for AI agents and coding assistants to search podcast transcripts and episode metadata, retrieve transcript excerpts, and generate citations. It requires no login or API key.

Enables AI assistants to query and analyze databases using natural language through MCP and HTTP API, supporting 17+ databases and integration with 50+ platforms.

Enables seamless integration with Weaviate vector databases, providing tools for semantic, keyword, and hybrid search across local or cloud instances. It supports schema management, collection retrieval, and multi-tenancy configurations through the Model Context Protocol.

AI-powered n8n documentation server that enables intelligent semantic search and retrieval of node configurations, workflows, and templates for AI assistants.

Routes requests to multiple downstream Model Context Protocol servers and provides a LangGraph.js-based agent with RAG capabilities for development assistance.

MCP server for NodeBB forums that enables AI assistants to access forum data, search topics, and perform semantic search via the Model Context Protocol.

Enables MCP clients to connect to LLM/API services using the Model Context Protocol, providing real-time interaction and tool access. Also offers RESTful API endpoints via FastAPI for programmatic integration with existing systems.

Serves an AI coding agent a searchable index of a codebase's existing capabilities and past incidents, so it can find and reuse what already exists before writing new code. Also exposes blast-radius analysis for shared code and lets the agent reindex the knowledge base, all via local retrieval with no model calls or API keys.

Enables MCP clients to query a self-hosted knowledge base through n8n RAG webhooks and Outline, supporting semantic search, full document reads, index health checks, and reindexing of Outline collections or repository Markdown.