How to Use the Ellie Planner MCP in CrewAI

Coordinate autonomous AI agent teams to organize and update your Ellie Planner timeline using CrewAI.

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Connect Ellie Planner MCP to CrewAI

Create your Vinkius account to connect Ellie Planner 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 Ellie Planner with CrewAI

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Automated task completion via specialized agents

`complete_task` allows your specialized coordination agent to close out items once dependencies are verified. In a CrewAI setup, a quality assurance agent can check a pull request and immediately mark the corresponding planning item as complete. This removes the need for manual updates. Your team's visual board stays perfectly synchronized with actual development progress, allowing project managers to see true status in real time.

Multi-agent task creation and planning

`create_task` lets your planning crew generate structured subtasks from a single high-level goal. A researcher agent drafts the requirements, while a manager agent executes this tool to populate your workspace with actionable steps. By delegating creation to autonomous agents, you avoid manual data entry. The crew populates titles, dates, and labels based on the context of the project, establishing a clear path forward.

Selective tool exposure for CrewAI teams

`list_tasks` retrieves current items so your monitoring agent can track overall progress. Using CrewAI's MCP tool filtering, you can expose this reading tool to your entire crew while restricting destructive actions to specific manager agents. This selective access secures your workspace. Your agents only interact with the specific tools they need, preventing rogue agents from accidentally modifying your planning board.

Setup guide

Set up Ellie Planner 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 Ellie Planner tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Ellie Planner 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="Ellie Planner Analyst",
        goal="Access and analyze Ellie Planner data via MCP.",
        backstory="Expert analyst with direct Ellie Planner access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Ellie Planner 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 Ellie Planner. 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.

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Common questions about Ellie Planner MCP in CrewAI

You can pass the URL directly in the agent's mcps list parameter during initialization. This instantly registers the tools for that specific agent without complex python setup.

Yes. Agents share context and can coordinate actions, meaning one agent can run `list_tasks` to find blockers while another runs `update_task` to reschedule them.

Use the MCPServerHTTP class from crewai.mcp with a tool filter. This lets you restrict access, ensuring a research agent cannot call `delete_task` during its run.

This server supports stdio, SSE, and Streamable HTTP transports. You can choose the protocol that best matches your crew's deployment environment.

Your task lists, due dates, and descriptions are only accessed during live agent execution. Vinkius runs the server in an ephemeral, zero-trust sandbox, so no planning data is ever stored or logged permanently.

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