CourtListener MCP Server for OpenAI Agents SDK 10 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect CourtListener through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MCPServerStreamableHttp(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as mcp_server:
agent = Agent(
name="CourtListener Assistant",
instructions=(
"You help users interact with CourtListener. "
"You have access to 10 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from CourtListener"
)
print(result.final_output)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About CourtListener MCP Server
Empower your AI agent to orchestrate your entire legal research workflow with CourtListener, the world's leading free and open platform for legal data. By connecting CourtListener to your agent, you transform complex legal searches into a natural conversation. Your agent can instantly search for opinions, audit court dockets, and retrieve detailed judge information without you ever touching a technical portal. Whether you are conducting case law research or monitoring judicial activity, your agent acts as a real-time legal assistant, ensuring your research is always grounded in open and accessible data.
The OpenAI Agents SDK auto-discovers all 10 tools from CourtListener through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries CourtListener, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
What you can do
- Opinion Auditing — Search for legal opinions by keyword and retrieve detailed metadata, including court name and date filed.
- Docket Oversight — Query court dockets to stay on top of ongoing litigation and case filings in real-time.
- Judicial Intelligence — Retrieve detailed information about judges and their financial disclosures to maintain strict control over your research context.
- Citation Discovery — List citations for specific opinions to understand the legal network and precedents.
- Court Governance — List all available courts and their metadata to ensure your jurisdictional research is accurate.
The CourtListener MCP Server exposes 10 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect CourtListener to OpenAI Agents SDK via MCP
Follow these steps to integrate the CourtListener MCP Server with OpenAI Agents SDK.
Install the SDK
Run pip install openai-agents in your Python environment
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Run the script
Save the code above and run it: python agent.py
Explore tools
The agent will automatically discover 10 tools from CourtListener
Why Use OpenAI Agents SDK with the CourtListener MCP Server
OpenAI Agents SDK provides unique advantages when paired with CourtListener through the Model Context Protocol.
Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety
Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure
Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate
First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output
CourtListener + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the CourtListener MCP Server delivers measurable value.
Automated workflows: build agents that query CourtListener, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries CourtListener, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through CourtListener tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query CourtListener to resolve tickets, look up records, and update statuses without human intervention
CourtListener MCP Tools for OpenAI Agents SDK (10)
These 10 tools become available when you connect CourtListener to OpenAI Agents SDK via MCP:
get_court
Get details for a specific court
get_judge
Get details for a specific judge
get_opinion
Get details for a specific opinion
list_citations
List citations for an opinion
list_courts
List all courts
list_financial_disclosures
List judge financial disclosures
list_judges
List judges
list_opinions
List opinions
search_dockets
Search for court dockets
search_opinions
Search for legal opinions
Example Prompts for CourtListener in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with CourtListener immediately.
"Search for court opinions about 'copyright fair use'."
"Show me details for judge ID 1234."
"Check for dockets related to 'SpaceX' in 2024."
Troubleshooting CourtListener MCP Server with OpenAI Agents SDK
Common issues when connecting CourtListener to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
CourtListener + OpenAI Agents SDK FAQ
Common questions about integrating CourtListener MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
Connect CourtListener with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
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GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect CourtListener to OpenAI Agents SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.