Langflow

Provides a bridge between Langflow and AI assistants, enabling flow management, execution, and monitoring via MCP tooling.
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6 months ago

First Indexed

2 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

You deploy and run an MCP server that bridges Langflow with AI assistants, enabling flows to be created, executed, and managed through conversational tooling. It provides structured access to Langflow features and lets you control flows, builds, imports/exports, knowledge bases, components, and monitoring from your MCP-enabled client.

How to use

You use this MCP server from an MCP client (such as Claude Desktop) to manage Langflow flows and run automations. Connect in stdio mode for local desktop clients or in http mode for remote access. In stdio mode, start the MCP server locally and point your client at the local process. In http mode, expose the MCP server on a port and secure it with a token to allow your client to communicate over HTTP.

How to install

# Prerequisites
- Node.js installed on your system
- A running Langflow instance
- Langflow API key

# Install from npm (global)
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 and usage notes

Prepare a local environment file to configure the server. The key settings include the Langflow base URL, API key, and the MCP mode. You can run in stdio mode for direct client integration or http mode for remote access.

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

Claude Desktop setup (stdio mode)

Add a configuration for Langflow MCP within Claude Desktop so you can issue MCP commands directly from Claude.

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

Alternative local installation command (stdio mode)

If you prefer running directly from a built distribution, place the MCP server start command in Claude Desktop as shown.

{
  "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"
      }
    }
  }
}

Docker deployment and quick start

You can run the MCP server in Docker for isolation and reproducibility. Use docker-compose for a quick start or build and run a standalone image for more control.

# Quick start with Docker (clone and docker-compose)
git clone https://github.com/nobrainer-tech/langflow-mcp.git
cd langflow-mcp

docker-compose up -d

docker-compose logs -f

docker-compose down

Building and running a Docker image

Build a standalone image and run in stdio mode locally or in http mode for remote access.

# 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 provided docker-compose setup supports both stdio and HTTP modes. Use the environment section to switch modes and set the base URL and API key.

# 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

Security and deprecated tools notes

If your setup exposes the MCP over HTTP, protect it with a strong token and restrict access to trusted clients.

The server includes deprecated tool endpoints by default. You can disable deprecated tools by setting ENABLE_DEPRECATED_TOOLS to false in your environment.

Troubleshooting and tips

Ensure your Langflow instance is reachable at the configured base URL and that the API key is valid. Check logs for connection errors and verify that the MCP_MODE matches your client (stdio for local desktop usage, http for remote access). If you change configuration, restart the MCP server to pick up new settings.

Available 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

run_flow

Execute a flow with input configuration (supports streaming)

trigger_webhook

Trigger a flow via webhook endpoint

upload_flow

Upload a flow from JSON data

download_flows

Download multiple flows as JSON export

get_basic_examples

Get pre-built example flows

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

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

list_variables

List all global variables

create_variable

Create a new variable

update_variable

Update variable properties

delete_variable

Delete a variable

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

list_knowledge_bases

List all available knowledge bases

get_knowledge_base

Get detailed information about a specific knowledge base

delete_knowledge_base

Delete a specific knowledge base

bulk_delete_knowledge_bases

Delete multiple knowledge bases at once

list_components

List all available Langflow components

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

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

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

build_vertices

(DEPRECATED) Get vertex build order for a flow

get_vertex

(DEPRECATED) Get details of a specific vertex/component

stream_vertex_build

(DEPRECATED) Stream real-time build events for a vertex

list_users

List all users (admin only)

get_current_user

Get current authenticated user info

get_user

Get details of a specific user

update_user

Update user profile information

reset_user_password

Reset password for a user (admin only)

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

list_custom_components

List all custom components

create_custom_component

Create a new custom component

login

Authenticate with username and password

auto_login

Auto-login with stored credentials

refresh_token

Refresh authentication token

logout

Logout and invalidate session

check_store

Check if component store is enabled

check_store_api_key

Validate a store API key

list_store_components

Browse available components in the store

get_store_component

Get details of a store component

list_store_tags

List all component tags in the store

get_user_likes

Get components liked by user

validate_code

Validate Python code for custom components

validate_prompt

Validate prompt template syntax

run_flow_advanced

Advanced flow execution with full control

process_flow

Legacy process endpoint for flows

predict_flow

Legacy predict endpoint for flows

get_public_flow

Get a public flow without authentication

batch_create_flows

Create multiple flows in one operation

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