How to Use the BallotReady MCP in Mastra AI

Build resilient civic data workflows by integrating the BallotReady MCP Server with Mastra AI.

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Connect BallotReady MCP to Mastra AI

Create your Vinkius account to connect BallotReady 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 BallotReady with Mastra AI

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Automate District Mapping Workflows

Wrapping `get_districts_by_address` in a Mastra workflow protects your batch jobs from API rate limits. Your automation keeps running even if the upstream connection stutters. If the tool fails to find a match, you configure the agent to branch the logic. It catches the error, falls back to a zip code search, or flags the record for manual review without crashing the entire batch process.

Monitor Ballot Measures via MCP Server

You configure a Mastra workflow to run `get_ballot_measures` on a cron schedule to track local propositions automatically. Tracking these filings usually requires constant polling across different municipalities. When the agent detects a new measure, it triggers a notification step. The `list_positions` tool confirms which offices are attached to the same ballot, giving your team a complete picture of the upcoming election cycle.

Audit Candidate Profiles

The `list_candidates` tool feeds raw challenger data directly into your automated campaign research pipelines. Political operatives need to know exactly who is running against them the moment papers are filed. Your agent pulls the list, then iterates through each name using `get_candidate` to build complete dossiers. Because Mastra handles the exponential backoff, you never have to write custom logic to deal with pagination limits.

Setup guide

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

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

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

Run the install command for the latest MCP package in your project folder. Instantiate the client with your endpoint URL and spread the listed tools into your agent's configuration.

You control exactly when the agent executes an action. Enable the approval requirement in your configuration to force a human-in-the-loop check before `get_elections_by_address` fires.

The framework detects the failure and applies exponential backoff automatically. It tries `get_officeholders` again with increasing delays until the request succeeds.

The client auto-detects between Streamable HTTP and SSE based on the endpoint. You just provide the URL and the framework handles the underlying connection details.

Every physical street location passes through a zero-trust execution environment. Vinkius strips all context after the `get_districts_by_address` operation completes, ensuring no residential information sits in a database.

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