UniCourt MCP Server for LlamaIndexGive LlamaIndex instant access to 27 tools to Delete Pacer Credential, Generate Token, Get Case, and more

Name: UniCourt
Price: 29 USD
Availability: InStock
Rating: 0.2 (1 reviews)
Author: Vinkius

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LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add UniCourt as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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The UniCourt MCP Server for LlamaIndex is a standout in the Data Management category — giving your AI agent 27 tools to work with, ready to go from day one.

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python

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

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to UniCourt. "
            "You have 27 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in UniCourt?"
    )
    print(response)

asyncio.run(main())

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About UniCourt MCP Server

Connect your UniCourt account to any AI agent to streamline legal research and litigation tracking through natural language.

LlamaIndex agents combine UniCourt tool responses with indexed documents for comprehensive, grounded answers. Connect 27 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

What you can do

Case Search — Search across millions of court cases using keyword expressions and filters
Automated Tracking — Use track_case to monitor specific litigation and receive updates on a schedule
Normalized Data — Access structured profiles for attorneys, law firms, judges, and parties to perform deep background checks
Document Management — Order court documents and export case data directly into your workflow
Legal Analytics — Retrieve case counts and analytics to understand litigation trends

The UniCourt MCP Server exposes 27 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 27 UniCourt tools available for LlamaIndex

When LlamaIndex connects to UniCourt through Vinkius, your AI agent gets direct access to every tool listed below — spanning court-records, legal-research, litigation-tracking, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

delete

Delete pacer credential on UniCourt

Delete PACER account credentials

generate

Generate token on UniCourt

Generate a new UniCourt access token

get

Get case on UniCourt

Get details for a specific case

get

Get case count analytics on UniCourt

Get case count analytics by case type

get

Get case export callback on UniCourt

Get the file URL for a completed case export

get

Get case update status on UniCourt

Check the status of a requested case update

get

Get document order callback on UniCourt

Get the file URL for a completed document order

get

Get norm attorney on UniCourt

Get analytics and details for a normalized attorney

get

Get norm judge on UniCourt

Get analytics and details for a normalized judge

get

Get norm law firm on UniCourt

Get analytics and details for a normalized law firm

get

Get norm party on UniCourt

Get analytics and details for a normalized party

get

Get pacer credential on UniCourt

Retrieve current PACER account credentials status

import

Import case on UniCourt

High-priority case import

import

Import pacer case on UniCourt

Import a case not in UniCourt via PACER

order

Order case document on UniCourt

Order a court document

request

Request case export on UniCourt

Request an export of case data as a ZIP file

request

Request case update on UniCourt

Request an asynchronous update for a case

Search cases on UniCourt

g., caseName:pfizer). Search for court cases

Search norm attorney on UniCourt

Search for normalized attorneys

Search norm judge on UniCourt

Search for normalized judges

Search norm law firm on UniCourt

Search for normalized law firms

Search norm party on UniCourt

Search for normalized parties

Search pacer case locator on UniCourt

Search PACER directly via Case Locator

track

Track case on UniCourt

Automatically update cases on a schedule

track

Track norm attorney on UniCourt

Schedule recurring bar source refreshes for an attorney

track

Track norm law firm on UniCourt

Schedule recurring source refreshes for a law firm

update

Update pacer credential on UniCourt

Manage PACER account credentials

Connect UniCourt to LlamaIndex via MCP

Follow these steps to wire UniCourt into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 27 tools from UniCourt

Why Use LlamaIndex with the UniCourt MCP Server

LlamaIndex provides unique advantages when paired with UniCourt through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine UniCourt tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain UniCourt tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query UniCourt, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what UniCourt tools were called, what data was returned, and how it influenced the final answer

UniCourt + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the UniCourt MCP Server delivers measurable value.

Hybrid search: combine UniCourt real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query UniCourt to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying UniCourt for fresh data

Analytical workflows: chain UniCourt queries with LlamaIndex's data connectors to build multi-source analytical reports

Example Prompts for UniCourt in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with UniCourt immediately.

"Search for court cases with the keyword 'Apple Inc' and sort by filing date."

"Set up automated tracking for case ID 1205934 with a daily refresh."

"Get the professional analytics for attorney ID ATTY-98765."

Troubleshooting UniCourt MCP Server with LlamaIndex

Common issues when connecting UniCourt to LlamaIndex through Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

UniCourt + LlamaIndex FAQ

Common questions about integrating UniCourt MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query UniCourt tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.

Does LlamaIndex support async MCP calls?

Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.

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