How do I find the Workspace ID for my Flow account?

You can use the 'list_workspaces' tool. The agent will retrieve all workspaces you have access to and return their names and unique IDs, which you can then use for other operations.

Can I mark a task as completed using the agent?

Yes! Use the 'update_task' tool, provide the Task ID, and set the 'status' parameter to 'completed'. The task will be immediately updated in Flow.

How do I see the discussion history for a task?

Use the 'list_task_comments' tool and provide the Task ID. The agent will retrieve all messages and replies associated with that task, allowing you to catch up on the discussion.

Flow MCP Server for LangChain 12 tools — connect in under 2 minutes

Name: Flow
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 12 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Flow through the Vinkius and LangChain agents can call every tool natively — combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "flow": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Flow, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

Fully ManagedVinkius Servers

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IAMAccess control

EU AI ActCompliant

DLPData protection

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Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Flow MCP Server

Connect your Flow account to any AI agent and automate your project management and team collaboration through the Model Context Protocol (MCP). Flow (getflow.com) provides a clean and powerful platform for organizing work, tracking task progress, and facilitating team discussions. Now, you can manage your workspaces, projects, and individual tasks directly through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Flow through native MCP adapters. Connect 12 tools via the Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures — with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

What you can do

Project Coordination — List all projects within your workspaces and retrieve detailed metadata, including ownership and due dates.
Task Management — Create, update, and list tasks across workspaces, projects, or specific task lists. Change statuses (incomplete/completed) instantly.
Organized Lists — Access and list task groups (Lists) within projects to maintain a clear hierarchy of work.
Team Interaction — List all workspace members and teams, and participate in task discussions by reading or adding comments.
Workspace Oversight — Get a high-level view of all the top-level workspaces you belong to.
Real-time Updates — Fetch specific task details or metadata to keep your team informed and your projects on track.

The Flow MCP Server exposes 12 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Flow to LangChain via MCP

Follow these steps to integrate the Flow MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 12 tools from Flow via MCP

Why Use LangChain with the Flow MCP Server

LangChain provides unique advantages when paired with Flow through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents — combine Flow MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Flow queries for multi-turn workflows

Flow + LangChain Use Cases

Practical scenarios where LangChain combined with the Flow MCP Server delivers measurable value.

RAG with live data: combine Flow tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Flow, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Flow tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Flow tool call, measure latency, and optimize your agent's performance

Flow MCP Tools for LangChain (12)

These 12 tools become available when you connect Flow to LangChain via MCP:

add_task_comment

create_task

Create a new task

get_project

Get project details

get_task

Get task details

list_projects

List projects in workspace

list_task_comments

List task discussions

list_task_lists

List lists in project

list_tasks

List tasks

list_workspace_members

List team members

list_workspace_teams

List workspace teams

list_workspaces

List top-level workspaces

update_task

). Update an existing task

Example Prompts for Flow in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Flow immediately.

"List all my Flow projects in the 'Marketing' workspace."

"Create a new task: 'Review final design mockup' in the 'Design' list."

"Add a comment to task 'task_123': 'Design looks great, proceed to coding'."

Troubleshooting Flow MCP Server with LangChain

Common issues when connecting Flow to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Flow + LangChain FAQ

Common questions about integrating Flow MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.