CourtListener MCP. Audit court dockets and judicial history via AI.
Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
CourtListener connects your AI agent to massive legal databases, letting you search court opinions, dockets, and judicial records in plain conversation.
It lets you audit case law by keyword or track ongoing litigation history without ever visiting a complex portal.
What your AI agents can do
Get court
Gets the detailed information for one specific court location or jurisdiction.
Get judge
Retrieves full background details for a single, specified judge.
Get opinion
Retrieves detailed metadata and text for a single, specific court opinion.
Retrieves specific metadata about any available court system.
Searches active court dockets to keep you updated on ongoing litigation and case movements.
Finds specific legal opinions by keyword, retrieving the full metadata like the filing date and originating court.
Gathers background information on judges, including their service dates and financial disclosures.
Lists all precedents or related cases tied to a specific published opinion.
Ask AI about this MCP
Supported MCP Clients
OAuth 2.0 CompatibleWaiting for input…
CourtListener: 10 Tools for Legal Data
These tools let your agent access specific data points across the entire spectrum of judicial records—from listing all courts to checking specific financial disclosures.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using CourtListener on Vinkius019d842aget court
Gets the detailed information for one specific court location or jurisdiction.
019d842aget judge
Retrieves full background details for a single, specified judge.
019d842aget opinion
Retrieves detailed metadata and text for a single, specific court opinion.
019d842alist citations
Lists all related citations to an opinion, helping you map the legal network.
019d842alist courts
Lists all available courts and their metadata to confirm your research scope.
019d842alist financial disclosures
Provides public records of financial disclosures made by a judge.
019d842alist judges
Provides lists of judges, which you can then use to narrow down your search context.
019d842alist opinions
Lists available legal opinions, allowing you to browse the scope of existing case law.
019d842asearch dockets
Searches active court dockets to see real-time status and filings for current cases.
019d842asearch opinions
Searches the entire repository of legal opinions using keywords or date ranges.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with CourtListener, then connect any of our 4,800+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,800+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
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- Works with Claude, ChatGPT, Cursor, and more
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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.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 10 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
The manual headache of tracking court cases today
Right now, finding case history means jumping through hoops: you start on a general court website, copy a case number, open another database for filings, then maybe jump to a third site just to check the judge's background. You end up with three different screenshots and a dozen tabs open.
With this MCP, your agent does all that work in one go. You tell it what you need—for example, 'Show me everything on case X.' The agent pulls together dockets, opinions, and necessary context without you ever touching a complex web portal.
Getting judicial history with CourtListener
You don't have to manually check multiple public records. The agent combines `list_judges` and `get_judge` automatically, giving you a clean profile. It also cross-references this data by allowing you to run `list_financial_disclosures` against any judge ID.
Now, your AI client provides a single source of truth that links judicial background directly to the legal rulings themselves.
What you can do with this MCP connector
Need to understand the background on a specific ruling? CourtListener runs an entire legal research workflow through your AI client. You stop jumping between separate court websites and start talking to a single agent that pulls data from open, authoritative sources. Your agent can find opinions based on keywords, check an individual judge’s history, or pull up a list of related cases.
It handles everything required to trace the full lineage of a legal concept.
This MCP is built for deep compliance and research. When your AI client compiles data from various tools, Vinkius tracks every single call through its cryptographically signed audit trail. This means you get verifiable proof of exactly where the information came from. Whether you are monitoring corporate litigation or verifying judicial disclosures, this tool ensures your legal context is always grounded in traceable records.
019d842a-9548-719d-ae13-505e890a3777 How CourtListener MCP Works
- 1 Subscribe to the MCP and enter your CourtListener API key.
- 2 Connect this service through your preferred client like Claude or Cursor.
- 3 Ask your agent to perform a complex query, such as 'Find all opinions regarding X by Judge Y'.
The bottom line is that you give the AI agent the prompt, and it executes the entire multi-step search process across the legal databases.
Who Is CourtListener MCP For?
This is for attorneys, compliance officers, and investigative journalists who deal with complex, high-stakes case law. If your job involves proving a point or tracking regulatory shifts, you need this.
Uses the MCP to track an opponent's dockets or research precedents for motions.
Checks judicial financial disclosures and court governance records to ensure adherence to regulatory standards.
Audits specific legal opinions, tracing their citations back through time to build a thesis on evolving law.
What Changes When You Connect
- Trace a full legal lineage: You can find an opinion using
search_opinions, then uselist_citationsto see every related precedent, building a complete picture of the law's evolution. - Monitor active litigation: Use
search_docketsto track ongoing case filings. This keeps you current on real-time legal movement without manual checks. - Vet judicial credibility: The MCP lets you cross-reference rulings with judge records using
list_financial_disclosures, ensuring your research context is clean and verifiable. - Establish jurisdiction: Start by running
list_courtsto confirm which specific courts are relevant. This prevents your agent from wasting time searching in the wrong jurisdiction. - Deep dive on rulings: After finding a general opinion list via
list_opinions, you can pull the full text usingget_opinionfor detailed analysis.
Real-World Use Cases
Investigating conflicts of interest
An investigator needs to know if a judge ruled on a case where they had a financial stake. They start by running list_judges, then find the specific judge, and use get_judge paired with list_financial_disclosures to check for conflicts before trusting any ruling.
Tracking corporate litigation
A legal team needs a summary of all recent filings against their client. They ask the agent to run search_dockets for the company name across multiple jurisdictions, getting an immediate status report on every active case.
Building a research paper
A student needs context for a specific legal concept. They use search_opinions to find initial rulings, then use list_citations repeatedly to map the entire body of supporting law and build their argument.
Verifying court scope
A firm is moving into a new region. They first call list_courts to get all available jurisdiction metadata, ensuring they use the correct legal framework for any future client work.
The Tradeoffs
Simple keyword search
Asking your agent only to 'Search opinions about copyright' and accepting the first few results. This ignores context.
→
Instead, use search_opinions to find candidates, then ask the agent to cross-reference those results with relevant judge data using get_judge to narrow down credibility.
Ignoring jurisdiction
Starting research without knowing which court handles the case. This leads to irrelevant or useless data.
→
Always start by running list_courts. The agent can use this list to confirm the proper governing body before you run any searches like search_dockets.
Treating opinions as isolated facts
Reading a single ruling and assuming it's the final word. This misses the surrounding legal context.
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After finding an opinion using get_opinion, you must immediately ask the agent to run list_citations on that record. That shows where the law comes from and what precedents support it.
When It Fits, When It Doesn't
Use this MCP if your legal research requires deep, verifiable context—if you need to know why a ruling was made or who wrote it. Don't use it if you just need general background knowledge (like 'What is the statute of limitations?'). For simple fact checking, that’s fine. But if you are trying to build an argument based on case law, this MCP is essential because it lets your agent trace everything from a judge's disclosure through to a specific opinion using multiple tools. Don't forget to check list_courts first; it grounds the entire process.
Common Questions About CourtListener MCP
How do I find my CourtListener API Key? +
Log in to your CourtListener account, and you will find your API Key under the API Tokens section. Copy and paste it below.
Can the agent search for both opinions and dockets? +
Yes. Use the search_opinions tool for legal judgments and search_dockets for case records. Your agent will return matching results from the Free Law Project database.
Is it possible to list judicial citations via the agent? +
Yes. The list_citations tool allows your agent to retrieve all precedents and subsequent citations for any opinion by providing its Opinion ID, helping you map the legal landscape.
How can I use the `list_courts` tool to determine my correct jurisdiction? +
You simply run the list_courts command. This pulls a complete catalog of all available courts in our database, letting you confirm your search area and ensure any dockets or opinions you retrieve are legally accurate for your region.
If I want to see a judge's financial history, is `list_financial_disclosures` the right tool? +
Yes, running list_financial_disclosures provides mandated public records of a judge’s assets and income. This lets researchers verify a judge's economic context or potential conflicts of interest directly within your workflow.
What information does `get_opinion` return for a specific case? +
It pulls comprehensive metadata about the legal opinion, including the court name, date filed, and often the full body of the argument. You get everything needed to understand the core precedent without leaving your agent environment.
What happens if I use `search_opinions` and don't find any results? +
The tool will return a clear message indicating no matches were found. This usually means you need to adjust the search parameters, such as broadening your date range or using more generalized keywords.
If I need details for multiple judges, is it better to use `list_judges` first? +
It’s best practice. You should use list_judges to get the names and IDs of all relevant personnel. Then you can loop through those IDs using get_judge to gather detailed profiles efficiently.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.