"A server for finding information about n8n workflow automation" matching MCP servers:

A Model Context Protocol server that exposes AI workflow templates as callable tools, enabling MCP clients to list templates, inspect their input/output schemas, and execute them synchronously or asynchronously to get structured results.

A standalone runtime and MCP server that executes Claude Code dynamic workflow files through interchangeable agent providers, ensuring compatibility with Claude Code's workflow format.

Enables users to submit goals via MCP so a host agent can generate scripts, coordinate subagents, monitor execution stages, recover interrupted runs, and deliver reusable artifacts.

A stateful MCP workflow engine that enforces strict step ordering for AI agents, persisting run state so interrupted workflows can be resumed from a checkpoint. It also supports parallel step groups, bounded retries, agent-chosen jumps between steps, rewinding, and a live browser dashboard across any MCP client.

Enables multi-agent code review and iterative improvement loop using different LLM backends, with deterministic scoring and audit trail.

Enables MCP clients such as Claude Desktop, Claude Code, and Cursor to discover node types, author and validate typed multi-agent workflow files, launch runs against a workspace, and retrieve run status, node outputs, and workspace change details.

Enables opencode clients to delegate a software-engineering task to a brigade of parallel subagents that split a DAG, implement in isolated shadow copies, machine-verify artifacts, pass review gates, and summarize results. It exposes asynchronous run, status, list, stop, and template tools for large refactors, batch fixes, and multi-option comparisons.

Enables AI agents to create and manage video compilations through n8n workflows with smart query optimization, quality analysis, batch processing, and trusted channel filtering for platforms like YouTube.

Enables AI agents to integrate with IBM Business Automation Workflow by exposing workflow REST services as MCP tools, allowing natural language interaction with business automation capabilities.

Enables AI agents to create, share, discover, and execute reusable multi-step workflow templates.

Run the open-source n8n-mcp locally and connect your n8n instance to MCP-compatible AI agents like Codex and Claude Code.

Enables AI coding agents to request a second opinion from a different frontier model via a single tool call, with PII scrubbed before transit, live web search, and support for Claude, ChatGPT, Cursor, and Gemini.

Enables AI agents to control a Playwright-driven browser through natural-language instructions, including page interaction and live browser task execution.

Enables multi-agent orchestration through a LangGraph supervisor and CrewAI-shaped crew, with in-process MCP tools and short- and long-term memory for research, tool use, and brief generation.

A production-grade multi-agent workflow orchestrator built on the Model Context Protocol, featuring planner/executor/critic agents, durable run state, and replayable traces.

Orchestrates multiple MCP tool calls into sequential workflows with conditional logic, data transformation via JSONPath, and workflow templates.

Enables AI agents to request an independent second opinion from a different frontier model, with PII scrubbing before transit, live web search grounding, caching, and multi-provider failover.

Enables ChatGPT to inspect Jobber data and manage controlled automations with scheduling, approval workflows, and audit trails.

Enables conversational agents and LLM clients to drive durable, multi-step business workflows over Streamable HTTP MCP with a strict four-state machine, atomic idempotency and replay, physical asset locking, and transactional notifications. Supports pluggable local SQLite or AWS DynamoDB/Step Functions backends while keeping workflow state authoritative across retries and network failures.

Enables MCP clients to run complete browser workflows through a single run_workflow tool, with anti-detection backends, intelligent element location, automatic retries, and session persistence.

Enables enterprise multi-agent decision workflows that expose 8+ MCP tools such as SQL query, web search, Python sandbox, RAG, file access, data cleaning, chart generation, and HTTP calls, orchestrated with LangGraph, streaming output, and human-in-the-loop approvals.

Guides AI agents through structured, multi-step workflows with discovery, navigation, and fidelity enforcement.

A Model Context Protocol server that enables AI assistants to interact with n8n workflows through natural language, supporting actions like listing, creating, updating, executing and monitoring workflows.

Enables deterministic, step-by-step execution of YAML-defined skills and workflows for AI agents, with progressive disclosure of active-step instructions and tools. It manages workflow state, conditional DAG transitions, loops, and persistent sessions via start_workflow, next_step, and end_workflow.

A Model Context Protocol server that enables AI agents to interact with n8n workflows and automation tools through a standardized interface, allowing execution of workflows and access to n8n functions.

Token-saving MCP proxy. Hides your MCP servers' tool lists behind a search tool and shrinks large tool results (GitHub, Playwright, logs, test output), keeping the full result available on request. One-command setup for Claude Code, Codex, Claude Desktop and Cursor.

A server implementation of the Model Context Protocol that enables calling iFlytek workflows, supporting complex orchestration modes like sequential, parallel, and looped execution across 14 node types for diverse business scenarios.

Enables ZCode to control a real Chrome browser, including tabs, navigation, page content, clicks, form filling, keyboard input, scrolling, screenshots, and JavaScript evaluation through a local MCP bridge.

Orchestrates Fireflies, Asana, and Notion MCP servers to automate end-to-end meeting workflows. Enables users to search meetings, extract action items, create tasks, and generate meeting documentation through natural language commands.

Enables OpenAI-compatible clients to access external tools, APIs, repositories, and data sources through MCP with allowlisting, approval, and argument validation, deployable as a FastAPI service or Python library.