How to Use the Bloomberg Law MCP in Mastra AI

Build complex legal workflows in Mastra AI with this managed Bloomberg Law MCP Server.

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Connect Bloomberg Law MCP to Mastra AI

Create your Vinkius account to connect Bloomberg Law 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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Setup Bloomberg Law with Mastra AI

Ask AI about this MCP

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Claude

Perplexity

Conditional legal workflows in Mastra AI

Trigger `search_federal_dockets` within your agent workflows to automate case monitoring. Mastra AI handles the retries if the network blips during a long-running research task. Set up branching logic so your agent acts on the output of `get_docket_details`. It turns static legal search into an active, decision-making process.

Automated expert witness research

Deploy an agent to find relevant experts using `search_expert_witnesses` for your ongoing litigation prep. It automates the discovery phase within your Mastra AI pipeline. Link this to `get_filing_document` to verify an expert's prior testimony. The framework manages the sequence of operations without manual intervention.

Business intelligence with Mastra AI

Use `search_companies` to pull entity profiles during your due diligence workflows. The MCP Server provides structured data that Mastra AI parses for your internal reports. Chain this with `search_legal_cases` to build a full picture of a company's litigation history. Everything stays within your defined agent logic.

Setup guide

Set up Bloomberg Law 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 Bloomberg Law 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: "bloomberg-law-mcp-client",
  servers: {
    "bloomberg-law-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

const result = await agent.generate(
  "List recent Bloomberg Law 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 Bloomberg Law. 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 Bloomberg Law MCP in Mastra AI

Add the server URL to your MCPClient definition in Mastra. The framework auto-discovers the tools so you can immediately add them to your agent's toolset.

Yes. Enable requireToolApproval in your Mastra config. You'll see the exact arguments passed to tools like `get_filing_document` before the agent runs them.

Mastra AI includes a workflow engine that handles retries. If a search fails, the agent can attempt the request again with the same parameters.

Vinkius isolates every session. We don't log your legal queries, and your research stays confined to the ephemeral sandbox provided by our infrastructure.

We use encrypted transports for all tool communication. No personally identifiable information from your research is retained on our servers.

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