# Langflow MCP for AI Agents AI Agent Connect > Langflow MCP for AI Agents. Orchestrate multi-agent workflows visually by running flows, managing projects, and triggering webhooks directly from your AI client. Connect your Langflow instance to give your agent the ability to execute complex RAG or multi-agent logic on command. ## Overview - **Category:** developer-tools - **Price:** Free - **Endpoint:** https://edge.vinkius.com/vk_preview_SsoeJOXDcMZ5NDD4MrW7XRXB6MCQXkWhm3WbCM4n/ai-agent-connect - **Tags:** multi-agent, ai-orchestration, visual-programming, langflow, workflow-automation ## Description You've spent hours building complex multi-agent workflows in Langflow, but now you're stuck with a UI that requires manual clicking for every single run. This Connector changes that by letting your AI client take the wheel. Instead of jumping back and forth between tabs, you can just tell your agent to trigger a specific flow or check the status of a background job. It turns your visual orchestration into an actionable set of commands. You can organize your work into projects, manage the lifecycle of your flows, and even handle external triggers through webhooks, all using natural language. It makes the bridge between your visual logic and your day-to-day execution much shorter. When you find this in the Vinkius catalog, you can connect once from any MCP-compatible client and get access to the entire catalog of tools to power your agentic workflows. You can iterate on your agent logic in real-time, query logs to see what went wrong, and keep your workspace organized. It's about giving your AI agent the keys to the automation you've already built. Whether you're testing a new RAG pipeline or managing a production-ready multi-agent system, this tool puts the controls in your chat window. You can stop hunting for the right buttons and start getting results. ## Tools ### create_project Make a new project folder to organize your work. This keeps your different experiments separated. ### create_response Use a flow_id as the model for an OpenAI-compatible response. This lets you treat a specific flow like a standard model. ### delete_file_v2 Remove a specific file from your system. Use this to clean up your storage and keep things tidy. ### delete_flow Remove a specific flow from your instance to keep your workspace clean. This helps you prune old tests or retired logic. ### delete_project Delete a project folder to remove old work. It's a fast way to clear out your project list. ### get_file_v2 Download a specific file associated with your flows. Use this to grab data or assets directly from the system. ### get_flow Fetch the details of a specific flow using its ID. This is useful for checking configurations without opening the UI. ### get_logs Retrieve recent logs to see how your flows are performing. You can use these to find errors in your agentic chains. ### get_monitor_messages Pull your chat history from the monitor. This lets you see the conversation flow in real time. ### get_monitor_traces Get execution traces and span trees for deep debugging. It shows you exactly how different components interacted. ### get_monitor_transactions View logs of interactions between different components. It's great for seeing the full lifecycle of a request. ### get_project Fetch the details of a specific project. Use this to see the contents and settings of your project folders. ### list_files_v1 List all files for a specific flow. This helps you see what assets are tied to a particular workflow. ### list_files_v2 See a list of all user files. Use this to get a high level view of your stored items. ### list_flows See a list of every flow you have created. This is the quickest way to see your available workflows. ### list_projects View all projects to see your organized workspace. It helps you keep your different workstreams separated. ### list_users See a list of all users on your instance. Use this for administrative oversight of your Langflow environment. ### run_flow Execute a flow using either chat or text inputs. This is the primary way to trigger your visual logic via your agent. ### run_workflow Start a workflow using the v2 API. This is ideal for running more complex, multi-step background jobs. ### trigger_webhook Start a flow run based on an external webhook event. Use this to connect your Langflow flows to other apps. ### update_flow Modify an existing flow's configuration. You can change logic or settings without having to rebuild the whole thing. ### whoami See the details of the currently authenticated user. This confirms your identity and permissions within the instance. ### update_project Change the information for a specific project. Use this to rename or re-categorize your project folders. ### create_flow Build a new flow from scratch. Use this to start a new visual agentic workflow immediately. ## Prompt Examples **Prompt:** ``` List all my available flows in Langflow. ``` **Response:** ``` I've retrieved your flows. You have 3 active flows: **Customer Support Agent** (ID: flow-123), **Data Extraction Pipeline** (ID: flow-456), and **Market Analyzer** (ID: flow-789). ``` **Prompt:** ``` Run the 'Market Analyzer' flow with the input 'Analyze NVIDIA stock performance'. ``` **Response:** ``` Executing **Market Analyzer**... The flow has completed. The analysis suggests a bullish trend for NVIDIA based on recent quarterly results and AI demand. ``` **Prompt:** ``` Show me all my project folders. ``` **Response:** ``` I found 2 projects: **Production Agents** (ID: proj-001) and **Experimental Lab** (ID: proj-002). ``` ## Capabilities ### Run specific flows Execute chat or text-based flows by name or ID directly from your agent. ### Manage project folders List and create project folders to keep your agentic workflows organized. ### Query execution logs Retrieve recent logs and traces to debug multi-agent behavior. ### Trigger webhooks Start flow runs in response to external events from other systems. ### Update flow logic Modify existing flows directly through your conversation. ### Download flow files Get specific files associated with your flows and projects. ## Use Cases ### Debugging a RAG pipeline An engineer asks their agent to check the logs for a specific flow to see why a retrieval failed. ### Project Organization A product lead asks the agent to list all projects to see which flows are currently in production. ### Automated Webhooks A developer sets up a trigger so that a flow runs every time a new lead is added to a CRM. ### Real-time Flow Updates A developer asks the agent to update a flow's configuration to point to a new database. ## Benefits - Run flows instantly without leaving your chat window by using run_flow. - Keep your workspace tidy by organizing workflows into folders with list_projects and create_project. - Debug multi-agent logic faster by pulling execution traces with get_monitor_traces. - Connect your AI to external systems using trigger_webhook for automated event responses. - Manage the entire lifecycle of your flows including updates and deletions with update_flow and delete_flow. - Access your data easily by downloading specific files using get_file_v2. ## How It Works The bottom line is you get to control your Langflow workflows using only plain English. 1. Subscribe to the Connector and enter your Langflow Base URL and API Key. 2. Connect your preferred client like Claude, Cursor, or Windsurf. 3. Start asking your agent to run flows, manage projects, or check logs. ## Frequently Asked Questions **What is the Langflow MCP for AI Agents?** It lets your AI client interact with your Langflow instance. You can run flows, manage projects, and check logs using just natural language. **Can I use the Langflow MCP to run multi-agent workflows?** Yes. It's designed specifically to let your agent execute complex flows and handle background jobs. **How do I organize my Langflow flows with this?** You can use your agent to create project folders and list them, keeping your agentic workflows structured and easy to find. **Can the Langflow MCP trigger flows from other apps?** Yes. It includes a tool to trigger webhooks, allowing you to start flows based on external events. **Can I debug my Langflow flows using an AI client?** You can. Your agent can retrieve recent logs and execution traces to help you see exactly where a flow might be failing. **Does the Langflow MCP support updating existing flows?** Yes. You can ask your agent to update a flow's configuration or a project's info directly through your conversation. **Can I run a flow using its name instead of a long UUID?** Yes! The `run_flow` tool accepts either the Flow ID or the Flow Name in the `flow_id` parameter, making it easy to trigger specific logic by name. **How do I see all the available projects and folders in my Langflow instance?** Use the `list_projects` tool. It will return a list of all projects (folders) which help organize your flows and components. **Is it possible to trigger a flow from an external webhook payload?** Absolutely. Use the `trigger_webhook` tool by providing the `flow_id` and the `data` JSON payload you want to send to the flow's entry point.