How to Use the Legal Fees Apportionment Engine MCP in LlamaIndex

Q: How do I index calculations from the Legal Fees Apportionment Engine in LlamaIndex?

You run the apportionlegalfees tool inside your agent, then index the resulting ledger output as a document node. This makes the exact award split searchable via semantic queries.

Q: Does the tool handle multi-party splits?

Yes. The apportionlegalfees tool splits awards among an arbitrary number of co-defendants based on their specific liability ratios.

Index and query exact judicial award distributions inside LlamaIndex.

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Connect Legal Fees Apportionment Engine MCP to LlamaIndex

Create your Vinkius account to connect Legal Fees Apportionment Engine to LlamaIndex 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 LlamaIndex

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Index legal fee splits directly into LlamaIndex

The `apportion_legal_fees` tool calculates the exact division of judicial awards and feeds the structured ledger directly into your vector store. Your RAG application can then query past settlement math without relying on LLM math guesses. This MCP Server connects your live calculations with your semantic search index. Instead of searching raw text files, you query the index for actual, mathematically verified fee distributions.

Ground legal RAG queries in verified math

The `apportion_legal_fees` tool ensures your agent answers questions about fee allocations using verified calculations rather than language model hallucinations. Your users get factual answers backed by an immutable ledger. When a user asks how much a specific defendant owes, LlamaIndex pulls the structured output of the calculation from the vector database. This workflow ensures that your natural language responses are always grounded in real math.

Build auditable legal knowledge bases

The `apportion_legal_fees` tool provides a complete audit trail of every deduction and percentage split. LlamaIndex stores this step-by-step breakdown as metadata in your document index. This setup lets you trace every calculation back to its source parameters. You can audit the exact liability percentages and contingency fee rates used in any historical case.

Setup guide

Set up Legal Fees Apportionment Engine MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Legal Fees Apportionment Engine MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Legal Fees Apportionment Engine tools.",
)
response = await agent.run("List recent Legal Fees Apportionment Engine data")

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Common questions about Legal Fees Apportionment Engine MCP in LlamaIndex

You run the `apportion_legal_fees` tool inside your agent, then index the resulting ledger output as a document node. This makes the exact award split searchable via semantic queries.

Yes. Because the engine outputs structured data, LlamaIndex indexes the mathematical results so your agent can retrieve exact billing figures later.

Install the required LlamaIndex MCP package, initialize the MCP client, and convert the tools using the tool spec. Your agent can then invoke `apportion_legal_fees` during query execution.

Yes. The `apportion_legal_fees` tool splits awards among an arbitrary number of co-defendants based on their specific liability ratios.

The MCP Server processes your attorney fee structures and award data in zero-trust, ephemeral sandboxes. No data is written to disk or retained after the tool execution completes.

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