Compatible with every major AI agent and IDE
What is the UniCourt MCP Server?
Connect your UniCourt account to any AI agent to streamline legal research and litigation tracking through natural language.
What you can do
- Case Search — Search across millions of court cases using keyword expressions and filters
- Automated Tracking — Use
track_caseto 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
How it works
- Subscribe to this server
- Enter your UniCourt Access Token
- Start querying legal records from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Legal Professionals — automate case monitoring and perform quick conflict checks
- Researchers — gather large-scale litigation data for market analysis
- Insurance & Finance — assess legal risks by inspecting party histories and active court cases
Built-in capabilities (27)
Delete PACER account credentials
Generate a new UniCourt access token
Get details for a specific case
Get case count analytics by case type
Get the file URL for a completed case export
Check the status of a requested case update
Get the file URL for a completed document order
Get analytics and details for a normalized attorney
Get analytics and details for a normalized judge
Get analytics and details for a normalized law firm
Get analytics and details for a normalized party
Retrieve current PACER account credentials status
High-priority case import
Import a case not in UniCourt via PACER
Order a court document
Request an export of case data as a ZIP file
Request an asynchronous update for a case
g., caseName:pfizer). Search for court cases
Search for normalized attorneys
Search for normalized judges
Search for normalized law firms
Search for normalized parties
Search PACER directly via Case Locator
Automatically update cases on a schedule
Schedule recurring bar source refreshes for an attorney
Schedule recurring source refreshes for a law firm
Manage PACER account credentials
Why LlamaIndex?
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.
- —
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 in LlamaIndex
UniCourt and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect UniCourt to LlamaIndex through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for UniCourt in LlamaIndex
The UniCourt 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. All 27 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in LlamaIndex only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.

* 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
How Vinkius secures
UniCourt for LlamaIndex
Every tool call from LlamaIndex to the UniCourt MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How can I search for court cases involving a specific company?
Use the search_cases tool with a query like caseName:"Company Name". The agent will return a list of matching cases with their UniCourt IDs and basic details.
Can the AI automatically track a case for new updates?
Yes! By using the track_case tool with a specific caseId, you can set up automated monitoring. You can even specify a refreshWindow like '1d' for daily updates.
Is it possible to get professional background data for an attorney?
Absolutely. Use search_norm_attorney to find the attorney and then get_norm_attorney with their ID to retrieve detailed analytics and professional history.
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.
BasicMCPClient not found
Install: pip install llama-index-tools-mcp
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