How to Use the CourtListener MCP in LlamaIndex

Q: How do I feed CourtListener data into LlamaIndex?

Install llama-index-tools-mcp. Wrap your HTTP endpoint in BasicMCPClient and pass it to McpToolSpec to extract the tools.

Q: Can LlamaIndex cache CourtListener opinions?

Yes, by indexing them. Once you pull a case via getopinion, it lives in your vector store for instant retrieval later.

Q: How do I restrict which CourtListener tools my agent uses?

Use the allowedtools filter when configuring your spec. You might allow searchopinions but block docket searches to keep the index focused.

Turn CourtListener case law into searchable vector stores by feeding LlamaIndex directly with live legal opinions.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect CourtListener MCP to LlamaIndex

Create your Vinkius account to connect CourtListener 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.

GDPR Free for Subscribers

Setup CourtListener with LlamaIndex

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Index Opinions for Semantic Search

Stop manually reading case text. LlamaIndex pulls full documents via `get_opinion` and chunks them into a queryable vector store. You ask plain questions. The engine scans the indexed legal text and returns answers grounded in actual case law, skipping the usual LLM hallucinations entirely.

LlamaIndex MCP Server for Court Data

Build a unified RAG application using `list_courts` and `list_judges`. The framework ingests the entire directory into your knowledge base for instant retrieval. When a user asks about a specific circuit's bench, the system queries the index instead of making fresh API calls. This drops latency significantly for repeated background checks.

Merge Internal Memos with Public Precedent

Combine your firm's private documents with live data from `search_opinions`. The `McpToolSpec` lets your FunctionAgent pull external citations on the fly. Set `include_resources=True` to grant direct data access to the MCP Server. Your knowledge base now updates itself whenever new rulings hit the public record.

Setup guide

Set up CourtListener 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 CourtListener 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 CourtListener tools.",
)
response = await agent.run("List recent CourtListener data")

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 CourtListener. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect CourtListener now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about CourtListener MCP in LlamaIndex

Install `llama-index-tools-mcp`. Wrap your HTTP endpoint in `BasicMCPClient` and pass it to `McpToolSpec` to extract the tools.

Yes, by indexing them. Once you pull a case via `get_opinion`, it lives in your vector store for instant retrieval later.

Use the `allowed_tools` filter when configuring your spec. You might allow `search_opinions` but block docket searches to keep the index focused.

That is the whole point of this MCP setup. The agent queries your local documents first, then reaches out to the server to fill in any missing legal precedent.

The Vinkius infrastructure runs your requests in an ephemeral V8 Isolate. The specific opinions, court details, and judge names you index are never logged on our servers. You handle the auth token, we handle the routing.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript