How to Use the Yodiz MCP in LangChain

Q: How do I get an overview of projects using Yodiz and LangChain?

You kick off the process by having your agent call listprojects. This tool pulls a list of all available agile projects, giving you the initial context needed for any subsequent step.

Q: Can I use Yodiz and LangChain to find active users?

Absolutely. Your agent calls listusers when it needs a roster of people in the workspace. This gives you all the necessary identifiers for filtering or checking permissions.

Q: What is the best way to track bugs with Yodiz and LangChain?

To find current issues, your agent uses listbugs. Just provide a project ID, and it returns all open bugs. This makes debugging workflows inside your LangChain chain much faster.

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Connect Yodiz MCP to LangChain

Create your Vinkius account to connect Yodiz 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.

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Setup Yodiz with LangChain

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Discover Project Scope

Need to know what projects exist? Start by running `list_projects`. This gives your agent a complete map of every agile initiative in the Yodiz account. From there, you can drill down. If the project ID is known, calling `list_epics` or `list_sprints` lets the chain build out the full feature structure for subsequent steps.

User and Bug Tracking

When your agent needs to validate who's involved, it calls `list_users`. This action provides a roster of every registered person in the Yodiz workspace. It also handles issue tracking. If something broke, running `list_bugs` immediately feeds the chain all current issues associated with a specific project ID.

Story and Iteration Management

Your agent can pinpoint exactly what work is needed by calling `list_user_stories`. You just need to supply the numeric project ID for this tool. Similarly, if you want to see upcoming deadlines, `list_sprints` pulls all scheduled iterations for a given Yodiz project. It’s perfect for sequential reasoning in your LangChain agent.

Setup guide

Set up Yodiz 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 Yodiz 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({
    "yodiz-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 Yodiz transactions"
    })
    print(result["messages"][-1].content)

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Common questions about Yodiz MCP in LangChain

You kick off the process by having your agent call `list_projects`. This tool pulls a list of all available agile projects, giving you the initial context needed for any subsequent step.

Absolutely. Your agent calls `list_users` when it needs a roster of people in the workspace. This gives you all the necessary identifiers for filtering or checking permissions.

To find current issues, your agent uses `list_bugs`. Just provide a project ID, and it returns all open bugs. This makes debugging workflows inside your LangChain chain much faster.

Yes. The MCP Server is designed to work across different project scopes. You can sequence calls, starting with `list_projects` and then targeting specific IDs for deeper dives into epics or stories.

This server touches user account information. Specifically, the `list_users` tool retrieves names and identifiers for all registered users in the workspace.

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