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Connect Langflow Visual Multi Agent Orchestrator to your AI

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Run and manage complex agentic workflows through natural conversation.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

A futuristic MCP client docking bay
V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 24 capabilities

We ship only the actions that matter.

Capability set01 / 06

01-04

4 capabilities in this set.

Part of 24 available through Langflow.

  1. 01

    Create response

    This capability provides an OpenAI compatible endpoint using a flow ID as the model.

  2. 02

    Get monitor transactions

    Retrieve logs regarding component interactions.

  3. 03

    Delete file v2

    Use this to remove a specific file from your Langflow instance.

  4. 04

    Delete flow

    This capability deletes an existing flow.

Capability set02 / 06

05-08

4 capabilities in this set.

Part of 24 available through Langflow.

  1. 05

    Get logs

    This capability retrieves recent system logs for debugging.

  2. 06

    Get monitor messages

    Retrieve your chat history through this capability.

  3. 07

    List files v2

    Retrieve a list of all user files.

  4. 08

    List flows

    This capability returns a list of all your available flows.

Capability set03 / 06

09-12

4 capabilities in this set.

Part of 24 available through Langflow.

  1. 09

    List projects

    Get a list of all your project folders.

  2. 10

    Run flow

    Execute a Langflow flow using either chat or text inputs.

  3. 11

    Run workflow

    This capability runs a workflow using the v2 API.

  4. 12

    Trigger webhook

    This capability starts a flow run by triggering a Langflow webhook.

Capability set04 / 06

13-16

4 capabilities in this set.

Part of 24 available through Langflow.

  1. 13

    Whoami

    Get information about your currently authenticated user.

  2. 14

    Create flow

    Create a brand new flow in your Langflow instance.

  3. 15

    Create project

    This capability creates a new project folder to organize your workflows.

  4. 16

    Delete project

    Use this to delete an entire project folder.

Capability set05 / 06

17-20

4 capabilities in this set.

Part of 24 available through Langflow.

  1. 17

    Get file v2

    This capability downloads a specific file from your instance.

  2. 18

    Get flow

    Get the details of a specific flow using its ID.

  3. 19

    Get monitor traces

    Use this to pull execution traces and span trees for debugging.

  4. 20

    Get project

    This capability retrieves the details of a specific project.

Capability set06 / 06

21-24

4 capabilities in this set.

Part of 24 available through Langflow.

  1. 21

    List files v1

    List the files associated with a specific flow.

  2. 22

    List users

    Retrieve a list of all users, provided you have superuser permissions.

  3. 23

    Update flow

    Use this to modify an existing flow.

  4. 24

    Update project

    This capability allows you to update project information.

Real work

What teams actually run

01

Rapid Prototyping

An engineer triggers a new flow to test a specific RAG logic change immediately.

02

Automated Monitoring

A developer checks recent logs to see why a specific agentic workflow failed.

03

System Integration

A DevOps lead triggers a Langflow webhook to kick off a workflow from an external event.

04

Workflow Organization

A product manager creates a new project folder to group related agent flows.

Automate a task

Put Langflow to work on one thing.

Step-by-step automations your AI runs through this Connector: the workflow, the prompts to start with, and the exact capabilities behind each move.

One connector, every AI

Langflow works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

Building your own app? The connector is yours to use.

You don't need a client to put Langflow to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

1022ms average. Fast in production.

Langflow is checked daily against the live service.

Daily averagePeak 1225ms
Oct 3Today
Fastest day
852ms
Slowest day
1225ms
14-day trend
Stable+4%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 24 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Langflow, so you can see the experience inside your AI.

It does not authenticate your account with Langflow. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Langflow Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_SsoeJOXDcMZ5NDD4MrW7XRXB6MCQXkWhm3WbCM4n/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Langflow capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "langflow-visual-multi-agent-orchestrator-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_SsoeJOXDcMZ5NDD4MrW7XRXB6MCQXkWhm3WbCM4n/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up Langflow in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Langflow owners hand off.

This MCP is built for technical teams building and managing complex agentic systems.

  • 01

    AI Engineers

    They use it to trigger and test RAG or multi-agent flows directly from their code editors.

  • 02

    Product Teams

    They use it to manage flow versions and project structures through natural language.

  • 03

    DevOps Leads

    They use it to connect visual AI logic to broader automation systems via webhooks.

FAQ

Questions Langflow owners ask.

  • 01

    How do I connect my Langflow instance?

    You subscribe to the MCP on Vinkius and enter your Langflow Base URL and API Key. Once connected, your AI client can immediately start interacting with your flows.

  • 02

    Can I run flows with text input?

    Yes, the run_flow capability supports both chat and text input types for executing your flows.

  • 03

    Is it possible to debug flows through my AI client?

    Yes, you can use capabilities like get_logs and get_monitor_traces to retrieve execution data and debug your agentic workflows.

  • 04

    Does this work with Cursor or VS Code?

    Yes, this MCP is compatible with any MCP-compatible client, including Cursor, Windsurf, and VS Code.

  • 05

    Can I organize my flows into folders?

    Yes, you can use the project management capabilities to create, list, and update project folders to keep your workflows structured.

  • 06

    Can I run a flow using its name instead of a long UUID?

    Yes! The run_flow capability accepts either the Flow ID or the Flow Name in the flow_id parameter, making it easy to trigger specific logic by name.

  • 07

    How do I see all the available projects and folders in my Langflow instance?

    Use the list_projects capability. It will return a list of all projects (folders) which help organize your flows and components.

  • 08

    Is it possible to trigger a flow from an external webhook payload?

    Absolutely. Use the trigger_webhook capability by providing the flow_id and the data JSON payload you want to send to the flow's entry point.

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