How to Use the Infinity Work Manager MCP in CrewAI

Q: How do I add the Infinity Work Manager tools to a CrewAI agent?

Use the MCPServerHTTP class from the CrewAI tools package. Pass your MCP URL directly into the agent's tool list.

Deploy a team of specialized CrewAI agents to coordinate, update, and manage your Infinity Work Manager boards autonomously.

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Connect Infinity Work Manager MCP to CrewAI

Create your Vinkius account to connect Infinity Work Manager 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.

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Setup Infinity Work Manager with CrewAI

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Multi-Agent Board Coordination with CrewAI

Let specialized agents divide and conquer your project management tasks. One agent can monitor high-level structures using `list_boards`, while another drills down into specific details. By sharing memory, the crew avoids redundant API calls. The researcher agent gathers data via `list_items`, and the editor agent executes `update_item` to keep things current.

Autonomous Backlog Grooming

Keeping a backlog clean is tedious, but a dedicated crew can do it overnight. Agents analyze task priorities using `list_attributes` and flag stale items. The moderator agent then uses `create_comment` to ask for updates or moves the task using `update_item`. This keeps your workspace clean without wasting developer time.

Hierarchical Workspace Setup via MCP Server

Setting up new projects requires consistent folder layouts and boards. Your crew can initialize entire workspaces autonomously using `create_board` and `create_folder`. The agents verify the setup by running `get_board` to confirm all custom fields are active. You get a perfectly organized workspace every single time.

Setup guide

Set up Infinity Work Manager 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 Infinity Work Manager tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

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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="Infinity Work Manager Analyst",
        goal="Access and analyze Infinity Work Manager data via MCP.",
        backstory="Expert analyst with direct Infinity Work Manager access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Infinity Work Manager 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 →

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Common questions about Infinity Work Manager MCP in CrewAI

Use the `MCPServerHTTP` class from the CrewAI tools package. Pass your MCP URL directly into the agent's tool list.

Yes, agents share the toolset and can execute tasks in parallel. The server handles concurrent requests for tools like `list_items` safely.

Yes, you can use CrewAI's tool filter to restrict access. For example, you can allow a researcher to use `get_item` but block them from `delete_item`.

The framework manages agent execution speed, but you should also configure rate-limiting middleware. This prevents parallel agents from flooding the API with `create_item` calls.

All workspace layouts, board names, and task descriptions pass through standard HTTPS encryption. The Vinkius MCP environment is completely stateless and never writes your data to disk.

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