MCP Connector

Manage and Execute Langflow Workflows

MCP server for Langflow with 209 tools (or 27 consolidated meta-tools) covering flows, execution, knowledge bases, RBAC, and more.

Works with langflow

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Updated last month
Version 4.10.0
Models
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Why it matters

Integrate AI assistants with the Langflow platform to manage, execute, and build complex automation workflows. This asset enables interaction with knowledge bases and comprehensive flow operations.

Outcomes

What it gets done

01

Create, list, get, update, and delete Langflow flows.

02

Execute flows via direct input or webhook triggers.

03

Manage flow build operations, including compilation and status monitoring.

04

Upload and download flows, and manage project organization.

Install

Add it to your toolbox

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/vb-langflow-mcp-server | bash

Capabilities

Tools your agent gets

create_flow

Create a new Langflow flow

list_flows

List all flows with pagination and filtering

get_flow

Get details of a specific flow by ID

update_flow

Update an existing flow

delete_flow

Delete a single flow

delete_flows

Delete multiple flows at once

run_flow

Execute a flow with input data configuration and streaming support

trigger_webhook

Trigger a flow via webhook

+7 tools

Overview

Langflow MCP Server

langflow-mcp-server bridges an AI assistant and Langflow, offering 209 granular tools or 27 consolidated meta-tools for flow management, execution, RAG knowledge bases, and RBAC administration. Use it to manage and run Langflow flows conversationally; switch to Consolidated Tools Mode to reduce token usage, and note Memory Bases are experimental.

What it does

langflow-mcp-server bridges AI assistants and the Langflow workflow automation platform, tracking Langflow API version 1.10.0 (including RBAC/authz, Memory Bases, Knowledge Base ingestion, extensions, and agentic sandbox files). It provides structured access to flow management (create/read/update/delete/execute), flow execution and webhooks, build compilation/validation/monitoring, import/export of flows and projects, folder/project organization, global variable configuration, Knowledge Base (RAG) management, and component discovery.

It ships in two modes: Standard (209 individual granular tools) and Consolidated Tools Mode (27 action-based meta-tools grouping related operations - e.g. a single flow tool covers list/get/create/update/delete/download/upload/replace/expand/batch/public actions), enabled via LANGFLOW_CONSOLIDATED_TOOLS=true to cut token usage and improve context management for AI assistants.

When to use - and when NOT to

Use this connector when you want an assistant to manage and run Langflow flows, build and monitor flow compilations, manage knowledge bases for RAG, or administer users/roles/authorization on a Langflow instance.

Do not use standard (209-tool) mode if you're tight on context budget - switch to Consolidated Tools Mode for the same functionality with far fewer tool definitions loaded. Note memory (Memory Bases) is flagged as an experimental Langflow API and may change.

Inputs and outputs

Tools take flow/folder/project IDs, flow input payloads, variable names/values, or knowledge-base documents depending on the operation. Outputs are Langflow API responses - flow definitions, execution results, build status, knowledge base contents, user/role data, or file operation confirmations.

Capabilities (Consolidated Tools Mode, 27 meta-tools)

  • flow / flow_execution / flow_version / build: full flow lifecycle, execution, versioning, and build operations
  • workflow / agentic: v2 workflow execution and agentic assistant/sandbox operations
  • folder / project / variable: organization and configuration management
  • knowledge_base / memory (experimental): RAG document ingestion and memory base management
  • file / file_v2: flow-scoped and user-scoped file operations
  • monitor / trace: build/session/transaction monitoring and execution tracing
  • model / authz / user / auth: model/provider config, RBAC, user management, authentication
  • store / registration / validation / mcp_server / mcp_project / extension / response / system: component store, registration, code/prompt validation, MCP server/project config, extensions, OpenAI-compatible responses, system health

How to install

npm install -g langflow-mcp-server

Or build from source:

git clone https://github.com/nobrainer-tech/langflow-mcp.git
cd langflow-mcp
npm install && npm run build
cp .env.example .env

Set in .env:

LANGFLOW_BASE_URL=http://localhost:7860
LANGFLOW_API_KEY=your-api-key-here

Add LANGFLOW_CONSOLIDATED_TOOLS=true for the reduced 27-tool mode. Requires Node.js 20+ and a running Langflow instance with an API key.

Who it's for

Teams building AI workflows in Langflow who want an assistant to manage, run, and monitor flows, knowledge bases, and users directly.

Source README

langflow-mcp-server

npm version
npm downloads
GitHub release
License: MIT
Tests
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A Model Context Protocol (MCP) server that provides AI assistants with comprehensive access to Langflow workflow automation platform.

Overview

langflow-mcp-server serves as a bridge between Langflow's workflow automation platform and AI models, enabling them to understand and work with Langflow flows effectively.

API Compatibility: This server is built on the Langflow API documentation and supports Langflow API version 1.10.0. Langflow 1.10.0 adds new endpoints (RBAC/authz, Memory Bases, the Knowledge Base ingestion overhaul, extensions, agentic sandbox files) on top of the 1.9.x surface without breaking existing routes; this release covers them.

Versioning: From 4.10.0 onward, the npm minor version mirrors the supported Langflow minor - langflow-mcp-server@4.<langflow_minor>.x targets Langflow 1.<langflow_minor>.x (so 4.10.x ↔ Langflow 1.10.x, a future 4.11.x ↔ Langflow 1.11.x). The patch component is used for fixes within the same Langflow minor.

Consolidated Tools Mode

Consolidated Tools Mode is an architecture that groups the 209 individual tools into 27 action-based meta-tools. This significantly reduces token usage and improves AI assistant context management.

Mode Tools Best For
Standard 209 tools Full granular control
Consolidated 27 tools Reduced token usage, better context

To enable consolidated mode:

LANGFLOW_CONSOLIDATED_TOOLS=true

Consolidated tools:

  • flow - All flow operations (list, get, create, update, delete, download, upload, replace, expand, batch, public, note_translations)
  • flow_execution - Run flows (run, run_advanced, run_session, webhook, process, predict)
  • flow_version - Flow versions and lifecycle events (list, create, get, delete, activate, get_events, create_event)
  • build - Build operations (start, status, cancel, vertices)
  • workflow - Run and manage v2 workflows (run with request-level globals, get_result, stop)
  • agentic - Agentic assistant + sandbox (assist, check_config, execute, get_file, reset_session)
  • folder - Folder management (list, get, create, update, delete, download, upload)
  • project - Project management (list, get, create, update, delete, download, upload)
  • variable - Variable operations (list, create, update, delete, detect)
  • knowledge_base - Knowledge base management (list, get, delete, bulk_delete, upload, create, preview/list chunks, ingest, cancel_ingest, test_connection, list_connectors, ingest_folder, ingest_connector, metadata_keys, list_runs, get_run)
  • memory - Memory bases (create, list, get, list_sessions, list_messages, update, delete, flush, mismatch, regenerate) - experimental Langflow API
  • file - Flow-scoped file operations (list, upload, download, delete, get_image)
  • file_v2 - User-scoped v2 files (list, upload, get, rename, delete, delete_all, batch_download, batch_delete)
  • monitor - Monitoring (builds, messages, sessions, transactions, job_queue)
  • trace - Execution traces (list, get, delete, delete_by_flow)
  • model - Models and providers (list, providers, enabled, default get/set/delete, mapping, validate, options)
  • authz - RBAC authorization (roles, role assignments, teams, shares, audit, my permissions)
  • user - User management (list, get_current, update, reset_password, create)
  • auth - Authentication (login, auto_login, logout, refresh, api keys, save_store_key)
  • store - Component store (list, get, tags, likes, save_api_key, create, like, update_custom)
  • registration - User registration (get, register)
  • validation - Code/prompt validation (code, prompt)
  • mcp_server - MCP server management (list, get, create, update, delete)
  • mcp_project - MCP project config/install (get/update config, get_installed, install, composer_url)
  • extension - Langflow extensions (reload, events)
  • response - OpenAI-compatible responses (create)
  • system - System info (health, version, logs, pictures, voices, session, webhook_events, health_check)

It provides structured access to:

  • Flow Management - Create, read, update, delete, and execute Langflow flows
  • Flow Execution - Run flows with inputs and trigger webhooks
  • Build Operations - Compile, validate, and monitor flow builds
  • Import/Export - Upload and download flows and projects
  • Organization - Manage folders and projects
  • Configuration - Manage global variables
  • Knowledge Bases - Manage RAG document collections
  • Component Discovery - List all available Langflow components

Quick Start

Prerequisites

  • Node.js 20 or newer installed on your system
  • A running Langflow instance
  • Langflow API key

Installation

# Install from npm
npm install -g langflow-mcp-server

# OR clone the repository
git clone https://github.com/nobrainer-tech/langflow-mcp.git
cd langflow-mcp

# Install dependencies
npm install

# Build the project
npm run build

# Configure environment
cp .env.example .env
# Edit .env with your Langflow instance URL and API key

Configuration

Edit .env file:

LANGFLOW_BASE_URL=http://localhost:7860
LANGFLOW_API_KEY=your-api-key-here
MCP_MODE=stdio
LOG_LEVEL=info

Claude Desktop Setup

Add to your Claude Desktop config file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
Linux: ~/.config/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "langflow": {
      "command": "npx",
      "args": ["-y", "langflow-mcp-server"],
      "env": {
        "LANGFLOW_BASE_URL": "http://localhost:7860",
        "LANGFLOW_API_KEY": "your-api-key-here",
        "LANGFLOW_CONSOLIDATED_TOOLS": "true",
        "MCP_MODE": "stdio",
        "LOG_LEVEL": "error"
      }
    }
  }
}

Alternative (local installation):

{
  "mcpServers": {
    "langflow": {
      "command": "node",
      "args": ["/absolute/path/to/langflow-mcp/dist/mcp/index.js"],
      "env": {
        "LANGFLOW_BASE_URL": "http://localhost:7860",
        "LANGFLOW_API_KEY": "your-api-key-here",
        "MCP_MODE": "stdio",
        "LOG_LEVEL": "error"
      }
    }
  }
}

Restart Claude Desktop after updating configuration.

Docker Deployment

The MCP server can be run in a Docker container for easier deployment and isolation.

Quick Start with Docker
# Clone the repository
git clone https://github.com/nobrainer-tech/langflow-mcp.git
cd langflow-mcp

# Create .env file with your configuration
cp .env.example .env
# Edit .env with your Langflow instance URL and API key

# Build and run with docker-compose
docker-compose up -d

# View logs
docker-compose logs -f

# Stop the server
docker-compose down
Building Docker Image
# Build the image
docker build -t langflow-mcp-server:latest .

# Run in stdio mode (for Claude Desktop)
docker run -it --rm \
  -e LANGFLOW_BASE_URL=http://localhost:7860 \
  -e LANGFLOW_API_KEY=your-api-key \
  langflow-mcp-server:latest

# Run in HTTP mode (for remote access)
docker run -d \
  -p 3000:3000 \
  -e MCP_MODE=http \
  -e PORT=3000 \
  -e AUTH_TOKEN=your-secure-token \
  -e LANGFLOW_BASE_URL=http://langflow:7860 \
  -e LANGFLOW_API_KEY=your-api-key \
  langflow-mcp-server:latest
Docker Compose Configuration

The included docker-compose.yml supports both stdio and HTTP modes:

# STDIO mode (default)
environment:
  - MCP_MODE=stdio
  - LANGFLOW_BASE_URL=http://localhost:7860
  - LANGFLOW_API_KEY=your-key

# HTTP mode
environment:
  - MCP_MODE=http
  - PORT=3000
  - AUTH_TOKEN=your-secure-token

Available MCP Tools

Once connected, Claude can use:

  • Standard mode: 209 individual tools
  • Consolidated mode: 27 action-based tools (recommended for reduced token usage)

Note: Raw MCP transport endpoints (SSE/streamable, /api/mcp/*) and doc-rendering
endpoints (/docs, /redoc, /openapi.json) are intentionally not exposed as
tools - they are protocol/transport surfaces, not data operations.

Standard Mode Tools (209 tools)

Flow Management (13 tools)

  • create_flow - Create a new Langflow flow
  • list_flows - List all flows with pagination and filtering
  • get_flow - Get details of a specific flow by ID
  • update_flow - Update an existing flow
  • delete_flow - Delete a single flow
  • delete_flows - Delete multiple flows at once
  • replace_flow - Replace a flow's full definition
  • expand_flows - Expand flows with embedded component data
  • upload_flow - Upload a flow from JSON data
  • download_flows - Download multiple flows as JSON export
  • get_basic_examples - Get pre-built example flows
  • batch_create_flows - Create multiple flows in one operation
  • get_public_flow - Get a public flow without authentication

Flow Execution (7 tools)

  • run_flow - Execute a flow with input configuration (supports streaming)
  • run_flow_advanced - Advanced flow execution with full control
  • run_flow_session - Execute a flow within a session context
  • trigger_webhook - Trigger a flow via webhook endpoint
  • get_webhook_events - Get webhook trigger events for a flow
  • process_flow - Legacy process endpoint for flows
  • predict_flow - Legacy predict endpoint for flows

Flow Versions & Events (7 tools)

  • list_flow_versions - List versions of a flow
  • create_flow_version - Create a new flow version
  • get_flow_version - Get a specific flow version
  • delete_flow_version - Delete a flow version
  • activate_flow_version - Activate a specific flow version
  • get_flow_events - Get lifecycle events for a flow
  • create_flow_event - Create a lifecycle event for a flow

Build Operations (6 tools)

  • build_flow - Build/compile a flow and return job_id for async execution
  • get_build_status - Poll build status and events for a specific job
  • cancel_build - Cancel a running build job
  • get_task_status - Get status of an async task
  • build_vertices - Get vertex build order for a flow
  • stream_vertex_build - Stream real-time build events for a vertex

Workflows (v2) (3 tools)

  • run_workflow - Run a v2 workflow
  • get_workflow_result - Get the result of a workflow run
  • stop_workflow - Stop a running workflow

Agentic (3 tools)

  • agentic_assist - Get agentic assistance for a flow component
  • agentic_check_config - Check whether agentic features are configured
  • agentic_execute - Execute an agentic flow by name

Responses (2 tools)

  • create_response - Create an OpenAI-compatible response
  • get_session - Get a response/conversation session

Folder Management (7 tools)

  • list_folders - List all folders with pagination
  • create_folder - Create a new folder
  • get_folder - Get folder details by ID
  • update_folder - Update folder name, description, or parent
  • delete_folder - Delete a folder
  • download_folder - Download entire folder as archive
  • upload_folder - Upload folder from archive

Project Management (7 tools)

  • list_projects - List all projects with pagination
  • create_project - Create a new project
  • get_project - Get project details by ID
  • update_project - Update project name or description
  • delete_project - Delete a project
  • upload_project - Upload a project from JSON data
  • download_project - Download a project as JSON export

Variable Management (5 tools)

  • list_variables - List all global variables
  • create_variable - Create a new variable
  • update_variable - Update variable properties
  • delete_variable - Delete a variable
  • detect_variables - Detect variables referenced in a value/template

Knowledge Base Management (11 tools)

  • list_knowledge_bases - List all available knowledge bases
  • list_knowledge_bases_detailed - List knowledge bases with detailed metadata
  • get_knowledge_base - Get detailed information about a specific knowledge base
  • create_knowledge_base - Create a new knowledge base
  • delete_knowledge_base - Delete a specific knowledge base
  • bulk_delete_knowledge_bases - Delete multiple knowledge bases at once
  • upload_knowledge_base - Upload a file to create/update a knowledge base
  • preview_knowledge_base_chunks - Preview how a document will be chunked
  • list_knowledge_base_chunks - List stored chunks for a knowledge base
  • ingest_knowledge_base - Ingest documents into a knowledge base
  • cancel_knowledge_base_ingest - Cancel an in-progress ingest job

File Management (5 tools)

  • upload_file - Upload a file to a specific flow
  • download_file - Download a file from a flow
  • list_files - List all files in a flow
  • delete_file - Delete a file from a flow
  • get_file_image - Get an image file from a flow

Files (v2) (8 tools)

  • list_files_v2 - List all user-scoped v2 files
  • upload_file_v2 - Upload a v2 file
  • get_file_v2 - Get v2 file metadata or content
  • rename_file_v2 - Rename a v2 file
  • delete_file_v2 - Delete a v2 file
  • delete_all_files_v2 - Delete all v2 files
  • batch_download_files_v2 - Download multiple v2 files
  • batch_delete_files_v2 - Delete multiple v2 files

Component Discovery & Custom Components (3 tools)

  • list_components - List all available Langflow components
  • create_custom_component - Create a new custom component
  • update_custom_component - Update an existing custom component

Monitoring & Analytics (12 tools)

  • get_monitor_builds - Get build execution history for a flow
  • get_monitor_messages - Query chat/message history with filtering
  • get_monitor_message - Get details of a specific message
  • update_monitor_message - Update a stored message
  • get_monitor_sessions - List all chat session IDs
  • get_monitor_session_messages - Get all messages for a session
  • migrate_monitor_session - Migrate messages between sessions
  • get_monitor_transactions - List transaction logs for a flow
  • delete_monitor_builds - Delete build history for a flow
  • delete_monitor_messages - Delete multiple messages by ID
  • delete_monitor_session_messages - Delete all messages for a session
  • delete_monitor_sessions - Delete chat sessions

Traces (4 tools)

  • list_traces - List execution traces with filters
  • get_trace - Get a specific execution trace
  • delete_trace - Delete a specific trace
  • delete_traces - Delete all traces for a flow

Shared Messages (5 tools)

  • get_shared_messages - Get shared messages
  • get_shared_sessions - Get shared sessions
  • update_shared_message - Update a shared message
  • migrate_shared_session - Migrate a shared session
  • delete_shared_session - Delete a shared session

Models & Providers (12 tools)

  • list_models - List available models
  • list_model_providers - List all model providers
  • list_enabled_providers - List enabled providers
  • list_enabled_models - List enabled models
  • set_enabled_models - Enable/disable models
  • get_default_model - Get the default model for a type
  • set_default_model - Set the default model for a type
  • delete_default_model - Remove the default model for a type
  • get_provider_variable_mapping - Get provider-to-variable mapping
  • validate_model_provider - Validate provider credentials
  • get_language_model_options - Get language model options
  • get_embedding_model_options - Get embedding model options

User Management (5 tools)

  • list_users - List all users (admin only)
  • get_current_user - Get current authenticated user info
  • update_user - Update user profile information
  • reset_user_password - Reset password for a user (admin only)
  • create_user - Create a new user (admin only)

API Key Management (3 tools)

  • list_api_keys - List all API keys for the user
  • create_api_key - Create a new API key
  • delete_api_key - Delete an API key

Authentication (4 tools)

  • login - Authenticate with username and password
  • auto_login - Auto-login with stored credentials
  • refresh_token - Refresh authentication token
  • logout - Logout and invalidate session

Registration (2 tools)

  • get_registration - Check whether registration is enabled
  • register_user - Register a new user account

Store & Marketplace (9 tools)

  • check_store - Check if component store is enabled
  • check_store_api_key - Validate a store API key
  • save_store_api_key - Save a store API key
  • list_store_components - Browse available components in the store
  • get_store_component - Get details of a store component
  • create_store_component - Publish a component to the store
  • like_store_component - Like a store component
  • list_store_tags - List all component tags in the store
  • get_user_likes - Get components liked by user

Validation (2 tools)

  • validate_code - Validate Python code for custom components
  • validate_prompt - Validate prompt template syntax

MCP Servers (v2) (5 tools)

  • list_mcp_servers - List MCP servers registered with Langflow
  • get_mcp_server - Get an MCP server by name
  • create_mcp_server - Create an MCP server
  • update_mcp_server - Update an MCP server
  • delete_mcp_server - Delete an MCP server

MCP Project Management (5 tools)

  • get_mcp_project_config - Get MCP config for a project
  • update_mcp_project_config - Update MCP config for a project
  • get_mcp_project_installed - Get installed MCP clients for a project
  • install_mcp_project - Install MCP for a project into a client
  • get_mcp_project_composer_url - Get the MCP composer URL for a project

Starter & Templates (1 tool)

  • list_starter_projects - List available starter templates

Profile & Media (2 tools)

  • list_profile_pictures - List available profile pictures
  • get_profile_picture - Get a specific profile picture

Integration Tools (1 tool)

  • list_elevenlabs_voices - List ElevenLabs text-to-speech voices

System & Health (4 tools)

  • get_version - Get Langflow API version information
  • health_check - Check Langflow instance health status
  • get_health_check - Get a detailed health-check report
  • get_logs - Retrieve system logs (supports streaming)

Authorization / RBAC (23 tools, Langflow 1.10.0)

  • list_authz_roles, get_authz_role, create_authz_role, update_authz_role, delete_authz_role - Manage roles
  • list_authz_role_assignments, create_authz_role_assignment, delete_authz_role_assignment - Manage role assignments
  • list_authz_teams, get_authz_team, create_authz_team, update_authz_team, delete_authz_team - Manage teams
  • list_authz_team_members, add_authz_team_member, remove_authz_team_member - Manage team members
  • list_authz_shares, get_authz_share, create_authz_share, update_authz_share, delete_authz_share - Manage resource shares
  • get_authz_audit - Query the authorization audit log (superuser)
  • get_my_permissions - Get the caller's effective permissions

Memory Bases (10 tools, Langflow 1.10.0 - experimental)

  • create_memory_base, list_memory_bases, get_memory_base - Manage memory bases
  • list_memory_base_sessions, list_memory_base_messages - Inspect tracked sessions/messages
  • update_memory_base, delete_memory_base - Update/delete a memory base
  • flush_memory_base, check_memory_base_mismatch, regenerate_memory_base - Lifecycle operations

Knowledge Base Overhaul (7 tools, Langflow 1.10.0)

  • test_knowledge_base_connection - Test a vector backend connection
  • list_knowledge_base_connectors - List available ingestion connectors
  • ingest_knowledge_base_folder, ingest_knowledge_base_connector - Ingest from a server folder or connector
  • get_knowledge_base_metadata_keys - List distinct metadata keys/values
  • list_knowledge_base_runs, get_knowledge_base_run - Inspect ingestion runs

Extensions & Misc (6 tools, Langflow 1.10.0)

  • reload_extension_bundle - Reload an extension bundle (requires server-side flag)
  • get_extension_events - Poll extension events for the current user
  • get_agentic_file - Read a file from the per-user agentic sandbox
  • reset_agentic_session - Reset agentic session/sandbox state
  • get_flow_note_translations - Get localized note-node translations for a flow
  • get_job_queue_metrics - Job-queue metrics snapshot (superuser)

The v2 workflow runner (run_workflow / workflow action run) also accepts request-level
globals (Langflow 1.10.0), the preferred replacement for the deprecated
X-LANGFLOW-GLOBAL-VAR-* headers.

Example Usage

// Create a new flow
create_flow({
  name: "My Automation Flow",
  description: "A flow that processes data"
})

// List all flows
list_flows({
  page: 1,
  size: 50
})

// Get flow details
get_flow({
  flow_id: "flow-uuid-here"
})

// Update a flow
update_flow({
  flow_id: "flow-uuid-here",
  name: "Updated Flow Name"
})

// Execute a flow
run_flow({
  flow_id_or_name: "my-flow-name",
  input_request: {
    input_value: "Hello World",
    output_type: "chat",
    input_type: "chat"
  },
  stream: false
})

// Trigger via webhook
trigger_webhook({
  flow_id_or_name: "my-flow",
  input_request: {
    input_value: "Process this data"
  }
})

// Build a flow (compile/validate)
build_flow({
  flow_id: "flow-uuid-here",
  log_builds: true,
  event_delivery: "polling"
})

// Check build status
get_build_status({
  job_id: "job-uuid-from-build",
  event_delivery: "polling"
})

// List knowledge bases (RAG)
list_knowledge_bases()

// Get knowledge base details
get_knowledge_base({
  kb_name: "my-documents"
})

// Create a folder
create_folder({
  name: "My Flows",
  description: "Organized flows"
})

// Create a project
create_project({
  name: "My Project",
  description: "Project description"
})

// Manage variables
create_variable({
  name: "API_KEY",
  value: "secret-key",
  type: "string"
})

// Get basic examples
get_basic_examples()

// List all components
list_components()

Development

# Build
npm run build

# Run in development mode
npm run dev

# Run tests
npm test

# Type checking
npm run typecheck

Project Structure

langflow-mcp/
├── src/
│   ├── mcp/
│   │   ├── index.ts       # MCP server entry point
│   │   ├── server.ts      # MCP server implementation
│   │   └── tools.ts       # Tool definitions
│   ├── services/
│   │   └── langflow-client.ts  # Langflow API client
│   ├── types/
│   │   └── index.ts       # TypeScript types
│   └── utils/
│       └── logger.ts      # Logging utility
├── .env.example           # Example configuration
├── package.json
├── tsconfig.json
└── README.md

Attribution

This project is inspired by and follows the structure of n8n-mcp by Romuald Czlonkowski. Special thanks to the n8n-mcp project for the excellent MCP server architecture and implementation patterns.

FAQ

Common questions

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