langflow-mcp-server

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 1.9.5.

Consolidated Tools Mode

Consolidated Tools Mode is an architecture that groups the 163 individual tools into 24 action-based meta-tools. This significantly reduces token usage and improves AI assistant context management.

Mode	Tools	Best For
Standard	163 tools	Full granular control
Consolidated	24 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)
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, get_result, stop)
agentic - Agentic assistant (assist, check_config, execute)
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)
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)
trace - Execution traces (list, get, delete, delete_by_flow)
model - Models and providers (list, providers, enabled, default get/set/delete, mapping, validate, options)
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)
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 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: 163 individual tools
Consolidated mode: 24 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 (163 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)

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.

License

MIT License - see LICENSE for details.

Contributing

Contributions are welcome! Please:

Fork the repository
Create a feature branch
Run tests (npm test)
Submit a pull request

Acknowledgments

Langflow team for the workflow automation platform
Anthropic for the Model Context Protocol
czlonkowski/n8n-mcp for the inspiration and architecture

Built with ❤️ for the Langflow community