CNJ (Datajud API Pública) MCP Server for Pydantic AIGive Pydantic AI instant access to 3 tools to Search Process By Number, Search Processes Advanced, Search Processes By Class And Organ

Name: CNJ (Datajud API Pública)
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect CNJ (Datajud API Pública) through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Ask AI about this MCP Server for Pydantic AI

Open in ChatGPT Open in Claude Open in Perplexity

The CNJ (Datajud API Pública) MCP Server for Pydantic AI is a standout in the Data Management category — giving your AI agent 3 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

+ other MCP clients

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to CNJ (Datajud API Pública) "
            "(3 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in CNJ (Datajud API Pública)?"
    )
    print(result.data)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 CNJ (Datajud API Pública) MCP Server

Connect to the CNJ Datajud Public API to perform deep searches across the Brazilian judicial system. This server allows AI agents to retrieve detailed metadata about lawsuits, court movements, and procedural history directly from the official national database.

Pydantic AI validates every CNJ (Datajud API Pública) tool response against typed schemas, catching data inconsistencies at build time. Connect 3 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Search by CNJ Number — Retrieve full details of a specific lawsuit using its unique unformatted numbering and the target court alias.
Class & Organ Filtering — Find processes categorized by their Procedural Class (TPU) and specific Court Organ codes.
Advanced Elasticsearch Queries — Execute complex searches using the full power of Elasticsearch Query DSL to filter by dates, parties, or specific metadata fields.
Court Coverage — Access data from various courts including TRFs, TJs, TST, and more via their respective API aliases.

The CNJ (Datajud API Pública) MCP Server exposes 3 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 3 CNJ (Datajud API Pública) tools available for Pydantic AI

When Pydantic AI connects to CNJ (Datajud API Pública) through Vinkius, your AI agent gets direct access to every tool listed below — spanning judicial-records, brazil-law, procedural-data, 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.

Search process by number on CNJ (Datajud API Pública)

g., api_publica_trf1, api_publica_tjsp). Search for a specific judicial process by its CNJ number

Search processes advanced on CNJ (Datajud API Pública)

Execute an advanced Elasticsearch query against the Datajud API

Search processes by class and organ on CNJ (Datajud API Pública)

Search processes by Procedural Class and Court Organ

Connect CNJ (Datajud API Pública) to Pydantic AI via MCP

Follow these steps to wire CNJ (Datajud API Pública) into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install Pydantic AI

Run pip install pydantic-ai

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 3 tools from CNJ (Datajud API Pública) with type-safe schemas

Why Use Pydantic AI with the CNJ (Datajud API Pública) MCP Server

Pydantic AI provides unique advantages when paired with CNJ (Datajud API Pública) through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your CNJ (Datajud API Pública) integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your CNJ (Datajud API Pública) connection logic from agent behavior for testable, maintainable code

CNJ (Datajud API Pública) + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the CNJ (Datajud API Pública) MCP Server delivers measurable value.

Type-safe data pipelines: query CNJ (Datajud API Pública) with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple CNJ (Datajud API Pública) tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query CNJ (Datajud API Pública) and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock CNJ (Datajud API Pública) responses and write comprehensive agent tests

Example Prompts for CNJ (Datajud API Pública) in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with CNJ (Datajud API Pública) immediately.

"Search for process number 50012345620234036100 in the TRF3 public API."

"List 5 processes from TJDFT with class code 1116 and organ code 12345."

"Run an advanced search in TST for processes moved in the last 7 days."

Troubleshooting CNJ (Datajud API Pública) MCP Server with Pydantic AI

Common issues when connecting CNJ (Datajud API Pública) to Pydantic AI through Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

CNJ (Datajud API Pública) + Pydantic AI FAQ

Common questions about integrating CNJ (Datajud API Pública) MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your CNJ (Datajud API Pública) MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.