How to Use the Docket Alarm MCP in Mastra AI

Q: How do I register the MCP Server tools within a Mastra AI agent?

Install the package using npm install @mastra/mcp@latest and instantiate the MCPClient pointing to your Vinkius endpoint. You then call mcpClient.listTools() and spread the resulting Docket Alarm tools directly into your agent's tool configuration array.

Q: Can I require manual lawyer approval before running Docket Alarm PACER searches in Mastra AI?

Yes, you can use Mastra's requireToolApproval flag on the searchpacer tool. This pauses the workflow and prompts a human reviewer to approve the action, preventing unexpected PACER transactional charges.

Q: How does Mastra AI handle state court search parameters for Docket Alarm?

The agent first calls getsearchdirectargs to verify the required fields for a specific state court. Mastra AI then validates the input data against this schema before executing searchdirect, preventing failed API calls.

Q: How is my firm's proprietary legal data secured during Mastra AI runs?

Every transaction involving extractjudgment or getcomplaintsummary executes inside an isolated, zero-trust sandbox. No litigation data, client names, or search queries are stored on the Vinkius platform, keeping your sensitive legal operations private.

Build resilient, self-healing legal workflows with Mastra AI and the Docket Alarm MCP Server.

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Create your Vinkius account to connect Docket Alarm to Mastra AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Resilient Tracking with Mastra AI

The `track_case` tool registers webhooks to monitor active litigation and trigger immediate updates when new filings occur. Within a Mastra AI workflow, you can chain this tracking tool to automatically run when a new matter is opened in your practice management system. If the court's API fails or rate-limits your request, the Mastra engine uses its built-in exponential backoff—automatically retrying the connection. This prevents missed deadlines and guarantees your case tracking remains active without manual developer intervention.

Extract Judgments and Causes of Action

The `extract_judgment` tool parses complex court orders to isolate rulings, damages, and prevailing parties. Mastra AI pipelines can pipe these extracted outcomes directly into `get_cause_of_action` to map the legal arguments that led to the judgment. You can build conditional branches using MCP tools that check if a judgment meets specific damage thresholds. If the extracted award exceeds a set dollar amount, the workflow routes the case details to senior litigation partners for immediate review.

Translate Conversational Queries

The `smart_search` tool converts conversational questions into precise, structured search strings for court databases. Mastra AI agents use this tool to interpret vague user requests and format them into syntax that state and federal search engines understand. This removes the need for paralegals to learn complex boolean search syntax. The agent runs the translated query through `search_direct` to scan state records, returning clean, structured results to your internal database.

Setup guide

Set up Docket Alarm MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All Docket Alarm tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "docket-alarm-mcp-client",
  servers: {
    "docket-alarm-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "Docket Alarm Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to Docket Alarm tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent Docket Alarm transactions"
);
console.log(result.text);

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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 Docket Alarm. 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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Common questions about Docket Alarm MCP in Mastra AI

Install the package using `npm install @mastra/mcp@latest` and instantiate the `MCPClient` pointing to your Vinkius endpoint. You then call `mcpClient.listTools()` and spread the resulting Docket Alarm tools directly into your agent's tool configuration array.

Yes, you can use Mastra's `requireToolApproval` flag on the `search_pacer` tool. This pauses the workflow and prompts a human reviewer to approve the action, preventing unexpected PACER transactional charges.

The agent first calls `get_search_direct_args` to verify the required fields for a specific state court. Mastra AI then validates the input data against this schema before executing `search_direct`, preventing failed API calls.

Mastra AI relies on its native workflow engine to handle transient court API failures. It automatically retries the `get_docket` call using configurable backoff strategies, ensuring temporary PACER outages do not break your legal automation pipelines.

Every transaction involving `extract_judgment` or `get_complaint_summary` executes inside an isolated, zero-trust sandbox. No litigation data, client names, or search queries are stored on the Vinkius platform, keeping your sensitive legal operations private.

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