How to Use the Legal Fees Apportionment Engine MCP in CrewAI

Coordinate autonomous legal teams in CrewAI using the Legal Fees Apportionment Engine.

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Connect Legal Fees Apportionment Engine MCP to CrewAI

Create your Vinkius account to connect Legal Fees Apportionment Engine 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 Legal Fees Apportionment Engine with CrewAI

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Role-based fee splitting in CrewAI

Assign the `apportion_legal_fees` tool to your analytical agent. While your research agent finds the liability percentages, your analyzer calculates the final split. This keeps your crew organized and efficient. Each agent handles one part of the legal process, and the math is handled by the dedicated tool.

Shared memory for legal agent teams

CrewAI agents can pass the results of the `apportion_legal_fees` tool to each other through shared memory. Your reporting agent can then draft a formal summary of the split. It eliminates the need for manual data entry between agents. Your crew acts as one unit, passing accurate numbers down the line.

Autonomous settlement monitoring

Set a monitor agent to watch for new judgment data and trigger the `apportion_legal_fees` tool automatically. Your crew handles the entire calculation without your input. You gain a constant, automated oversight of your settlement ledger. It frees your time to focus on strategy rather than repetitive math.

Setup guide

Set up Legal Fees Apportionment Engine 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 Legal Fees Apportionment Engine tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Legal Fees Apportionment Engine 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 Legal Fees Apportionment Engine MCP in CrewAI

Pass the server endpoint directly into your agent's configuration. Your crew will automatically recognize the `apportion_legal_fees` tool for their tasks.

Yes. You can assign the tool to one specific agent or share it across the entire crew. It works seamlessly in both sequential and hierarchical setups.

It provides a single source of truth for all fee-related math. Agents can rely on the deterministic output of the tool to make informed decisions.

It is designed for autonomous use. Once configured, your agents can pull the necessary data and run the calculations independently.

All calculations are performed in a zero-trust, ephemeral environment. The server discards your inputs immediately after the math is complete, ensuring your data remains isolated.

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