How to Use the Float MCP in CrewAI

Q: How do I add the Float MCP Server to my CrewAI agents?

Pass the server URL into the mcps parameter of your Agent configuration. This immediately grants your crew access to all twelve scheduling tools.

Q: Can CrewAI agents modify Float data independently?

Yes, provided they have access to tools like createallocation. You can filter these tools to restrict which agents have write permissions, keeping your project data secure.

Deploy a specialized crew of agents in CrewAI to manage your Float resource allocations autonomously.

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Connect Float MCP to CrewAI

Create your Vinkius account to connect Float 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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Role-based scheduling with CrewAI

Assign a 'Scheduler' agent to use `list_allocations` and a 'Reporter' agent to use `get_logged_time`. They collaborate using shared memory to keep the team on track. Different agents handle different parts of the project lifecycle. This specialization ensures that one agent focuses on capacity while the other manages project completion.

Autonomous task management via MCP Server

Let your crew execute `create_allocation` based on incoming project tickets. The agents evaluate the resource pool and make the best assignment decisions. It turns a manual chore into a background task. You set the strategy, and the agents execute the work across your Float account.

Cross-departmental resource visibility

Use `list_departments` and `list_people` to give your crew a full view of your organization. They can balance loads across teams without human intervention. It’s not just about scheduling one person. It’s about understanding the entire resource capacity and moving tasks to where they fit best.

Setup guide

Set up Float 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 Float tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Float 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 Float. 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 Float MCP in CrewAI

Pass the server URL into the `mcps` parameter of your Agent configuration. This immediately grants your crew access to all twelve scheduling tools.

Yes, provided they have access to tools like `create_allocation`. You can filter these tools to restrict which agents have write permissions, keeping your project data secure.

If you have a large crew, you might hit limits. We recommend using a sequential execution pattern to space out your tool calls and keep the agent traffic within acceptable bounds.

It is. You can have a manager agent oversee the output of junior agents, ensuring that every allocation made via the MCP Server aligns with your high-level project goals.

Your Float data is isolated from other users in a zero-trust environment. Every request is scoped to your token, and the ephemeral nature of the server means your team's names and time-off records are never stored beyond the active session.

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