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
Dozens of tools overlap heavily: run_flow, run_flow_advanced, run_flow_session, process_flow, predict_flow, run_workflow, run_public_workflow, agentic_execute, invoke_a2a_jsonrpc, and create_response all execute flows with subtly different semantics. Duplicate surfaces also exist (list_files vs list_files_v2, build_flow vs build_public_flow vs build_vertices, health_check vs get_health_check vs get_healthz). An agent cannot reliably choose among these.
Naming Consistency3/5
Most names follow snake_case verb_noun, but conventions drift across domains: get_health_check vs health_check vs get_healthz, check_store vs check_memory_base_mismatch, and many versioned aliases (_v2, _advanced, _session). It's readable but not predictable.
Tool Count1/5
236 tools is an extreme mismatch for a coherent MCP surface, far beyond practical agent selection. The set appears to expose nearly the entire Langflow REST API including deprecated and experimental endpoints.
Completeness4/5
Coverage is extremely broad across flows, folders, projects, knowledge bases, authz, models, MCP servers, and monitoring, so few domain gaps remain. The main issue is overwhelming duplication and legacy aliases rather than missing operations.
Maintenance
ActivityActive
ResponsivenessUnresponsive