A
licenseB
qualityC
maintenanceA Model Context Protocol server that enables AI assistants to interact with N8N workflows, executions, and automation capabilities.
12
MIT
langflow-mcp-server
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TDQS
C2.9/5.0
Scored across 236 tools
Disambiguation1/5
With 236 tools including many overlapping execution endpoints (run_flow, run_flow_advanced, run_workflow, run_flow_session, process_flow, predict_flow, agentic_execute, invoke_a2a_jsonrpc, run_public_workflow, run_workflow, trigger_webhook) and multiple file APIs (list_files, list_files_v2, upload_file, upload_file_v2), agents will struggle to pick the correct tool. Different entity families are also mixed under similar prefixes (authz roles/teams/shares vs. users).
Naming Consistency3/5
The tool names mostly follow a readable verb_noun snake_case pattern. However, there are mixed verb styles (get vs list vs run vs build vs start), a few awkward names like 'agentic_check_config', and version suffixes (_v2) that break the pattern.
Tool Count1/5
236 tools is an extreme mismatch for a cohesive server surface and far beyond typical toolset sizes. This volume forces agents to navigate a sprawling API dump, making selection error-prone and context unwieldy.
Completeness4/5
The tool surface is extremely comprehensive, covering flows, folders, projects, users, authz, knowledge bases, models, MCP, traces, and more, with CRUD for most entities. It is arguably over-complete rather than missing major operations.
Maintenance
ActivityActive
ResponsivenessUnresponsive