How to Use the KanbanTool MCP in LangChain

Q: How do I use LangChain to create a new KanbanTool task?

First, get the tools into your agent using client.gettools(). Then just prompt it: "Create a task on the 'Backend' board called 'Fix API bug'." Your agent will know to use the createtaskcard tool.

Q: Can my LangChain agent move KanbanTool cards between columns?

Yes. The agent just needs to call updatetaskdetails with the task ID and the target columnname. It's a single, simple action in a chain.

Q: Can I build a chain that archives old tasks in KanbanTool with LangChain?

Absolutely. Your agent can listboardtasks, loop through them, check the last update time with listtaskactivities, and then call archivetaskcard on any task that meets your inactivity rules.

Build LangChain agents that chain KanbanTool actions, turning complex board management into a single, automated flow.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect KanbanTool MCP to LangChain

Create your Vinkius account to connect KanbanTool to LangChain and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup KanbanTool with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Chain Automated Board Audits

This MCP Server lets your agent run a full audit without you lifting a finger. Start a chain with `list_boards` to get a complete inventory. For each board, the agent can then call `list_board_tasks` to check for stale cards, using `list_task_activities` to pinpoint the last update. Based on your rules, the agent decides the next step. If a card is inactive for 14 days, the chain can trigger `update_task_details` to post a warning comment. If it's 30 days, the agent calls `archive_task_card` to clean house. It’s a complete, self-running process.

Generate Live Status Reports

Stop manually compiling updates for stand-up. A LangChain agent can do it for you. The agent starts by calling `get_board_details` for a high-level view, then uses `list_board_tasks` to pull all tasks assigned to a specific person. From there, it can fetch recent updates on each task with `list_task_activities` and assemble a clean summary. The agent can even find the board's public URL with `list_shared_links` and include it in the final report, delivering it to you in Slack or email.

Manage Tasks Across Multiple Boards

Moving tasks between projects is tedious. Use a LangChain agent to handle it. The agent can use `get_task_details` to pull all the information from a card on one board—description, assignee, labels, everything. Then, it immediately calls `create_task_card` to replicate that task on a different board. This is perfect for promoting a task from a 'Product Backlog' board to the 'Current Sprint' board, ensuring no context is lost along the way.

Setup guide

Set up KanbanTool MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes KanbanTool tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

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

async with MultiServerMCPClient({
    "kanbantool-mcp": {
        "transport": "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,
    )
    result = await agent.ainvoke({
        "messages": "List recent KanbanTool transactions"
    })
    print(result["messages"][-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by KanbanTool. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect KanbanTool now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about KanbanTool MCP in LangChain

First, get the tools into your agent using `client.get_tools()`. Then just prompt it: "Create a task on the 'Backend' board called 'Fix API bug'." Your agent will know to use the `create_task_card` tool.

Yes. The agent just needs to call `update_task_details` with the task ID and the target `column_name`. It's a single, simple action in a chain.

Every tool call is automatically traced in LangSmith. You'll get full observability into the inputs and outputs for `get_board_details`, `update_task_details`, and any other tool your agent uses. No extra setup required.

Absolutely. Your agent can `list_board_tasks`, loop through them, check the last update time with `list_task_activities`, and then call `archive_task_card` on any task that meets your inactivity rules.

Your KanbanTool data—task details, board names, user profiles—is passed directly from the Vinkius-managed MCP server to the KanbanTool API. Vinkius infrastructure is ephemeral and does not log or store your board content. Your LangChain agent just coordinates the API calls.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript