How to Use the Yodiz MCP in CrewAI

Q: How do I get a full project breakdown using Yodiz and CrewAI?

You set up a crew where one agent calls listprojects, and a second, specialized agent then uses those IDs to call listsprints. The process runs sequentially.

Q: Can the MCP Server handle listing user stories for Yodiz using CrewAI?

Yes. You give an agent access to listuserstories and a project ID. This is perfect for building automated operational reports on feature requirements.

Q: What if I need to check bugs in Yodiz using CrewAI?

You assign a bug-checking agent with access to listbugs. It runs the tool, gathering all issues for the specified project into shared memory for subsequent analysis.

Build autonomous Yodiz operations using the CrewAI multi-agent framework.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Yodiz MCP to CrewAI

Create your Vinkius account to connect Yodiz to CrewAI 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 Yodiz with CrewAI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Run Autonomous Project Discovery

The `list_projects` tool allows a specialized agent to gather all agile projects in your Yodiz account. A monitoring agent can watch this process, ensuring the full list is captured. A subsequent agent then takes those project names and uses them to run `list_sprints`, establishing an autonomous sequence of data gathering.

Analyze User Stories via MCP Server

A dedicated analysis agent can run `list_user_stories` for a given project ID, collecting all the necessary story details. This process is highly specialized and shares memory across agents. A second agent can then take those stories, cross-referencing them with `list_epics`, to build out a comprehensive view of the feature scope.

Monitor Bugs and Users for Yodiz

You'll use a combination of tools like `list_bugs` and `list_users`. The crew runs these sequentially: one agent gets the bug list, another gets the user list. This simulates an operational audit. The monitoring agent keeps track of both data sets, ensuring nothing is missed in the final output.

Setup guide

Set up Yodiz MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Yodiz tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Yodiz Analyst",
    goal="Access and analyze Yodiz data via MCP.",
    backstory="Expert analyst with direct Yodiz access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Yodiz transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Yodiz Analyst",
        goal="Access and analyze Yodiz data via MCP.",
        backstory="Expert analyst with direct Yodiz access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Yodiz transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

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 Yodiz. 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 Yodiz 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 Yodiz MCP in CrewAI

You set up a crew where one agent calls `list_projects`, and a second, specialized agent then uses those IDs to call `list_sprints`. The process runs sequentially.

Yes. You give an agent access to `list_user_stories` and a project ID. This is perfect for building automated operational reports on feature requirements.

You assign a bug-checking agent with access to `list_bugs`. It runs the tool, gathering all issues for the specified project into shared memory for subsequent analysis.

It supports multi-agent collaboration. You can build a system where one agent calls `list_users` and another immediately summarizes that data, all autonomously.

The server handles Project IDs, User Names, and Bug details. The crew ensures this read-only information is processed and reported without exposing it outside your controlled environment.

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