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OpenFEC (Federal Election Commission) MCP Server for Mastra AIGive Mastra AI instant access to 21 tools to Get Candidate, Get Candidate History, Get Candidate Totals, and more

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Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect OpenFEC (Federal Election Commission) through Vinkius and Mastra agents discover all tools automatically. type-safe, streaming-ready, and deployable anywhere Node.js runs.

Ask AI about this MCP Server for Mastra AI

The OpenFEC (Federal Election Commission) MCP Server for Mastra AI is a standout in the Data Analytics category — giving your AI agent 21 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

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

async function main() {
  // Your Vinkius token. get it at cloud.vinkius.com
  const mcpClient = await createMCPClient({
    servers: {
      "openfec-federal-election-commission": {
        url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
      },
    },
  });

  const tools = await mcpClient.getTools();
  const agent = new Agent({
    name: "OpenFEC (Federal Election Commission) Agent",
    instructions:
      "You help users interact with OpenFEC (Federal Election Commission) " +
      "using 21 tools.",
    model: openai("gpt-4o"),
    tools,
  });

  const result = await agent.generate(
    "What can I do with OpenFEC (Federal Election Commission)?"
  );
  console.log(result.text);
}

main();
OpenFEC (Federal Election Commission)
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 OpenFEC (Federal Election Commission) MCP Server

Connect to the official OpenFEC API and bring transparency to federal election data through your AI agent. This server provides direct access to the Federal Election Commission's comprehensive database of campaign finance information.

Mastra's agent abstraction provides a clean separation between LLM logic and OpenFEC (Federal Election Commission) tool infrastructure. Connect 21 tools through Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution. deployable to any Node.js host in one command.

What you can do

  • Candidate Research — List and search for individuals running for President, Senate, or House with filters for state, party, and cycle.
  • Financial Analytics — Retrieve aggregated financial totals and summaries for specific candidates to understand fundraising and spending.
  • Committee Tracking — Explore political committees (PACs, party committees) and their detailed metadata and filings.
  • Historical Context — Access the history of candidate filings and designations over multiple election cycles.
  • Deep Metadata — Fetch detailed profiles for any candidate or committee using their unique FEC identifiers.

The OpenFEC (Federal Election Commission) MCP Server exposes 21 tools through the Vinkius. Connect it to Mastra AI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 21 OpenFEC (Federal Election Commission) tools available for Mastra AI

When Mastra AI connects to OpenFEC (Federal Election Commission) through Vinkius, your AI agent gets direct access to every tool listed below — spanning campaign-finance, election-data, political-transparency, 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.

get

Get candidate on OpenFEC (Federal Election Commission)

Get detailed information for a specific candidate by ID

get

Get candidate history on OpenFEC (Federal Election Commission)

Get the history of a candidate filings and designations

get

Get candidate totals on OpenFEC (Federal Election Commission)

Get aggregated financial totals for a specific candidate

get

Get committee on OpenFEC (Federal Election Commission)

Get detailed information for a specific committee by ID

get

Get committee history on OpenFEC (Federal Election Commission)

Get the history of a committee characteristics over time

get

Get totals by committee type on OpenFEC (Federal Election Commission)

Get financial totals for a specific committee type

get

Get totals by entity on OpenFEC (Federal Election Commission)

Get financial totals aggregated by candidate or committee entity

get

Get totals officer summary on OpenFEC (Federal Election Commission)

Summarize financial data by committee officer

list

List candidates on OpenFEC (Federal Election Commission)

Fetch a list of candidates with various filters

list

List committees on OpenFEC (Federal Election Commission)

Fetch a list of committees with filters

list

List filings on OpenFEC (Federal Election Commission)

List all filings (electronic and paper) with filters

list

List reports on OpenFEC (Federal Election Commission)

Fetch financial reports filed by specific types of committees

list

List schedule a on OpenFEC (Federal Election Commission)

Itemized Receipts: Contributions from individuals and committees

list

List schedule b on OpenFEC (Federal Election Commission)

Itemized Disbursements: Operating expenditures, transfers, refunds

list

List schedule c on OpenFEC (Federal Election Commission)

Loans: Information on loans received or made by committees

list

List schedule d on OpenFEC (Federal Election Commission)

Debts: Debts and obligations owed by or to committees

list

List schedule e on OpenFEC (Federal Election Commission)

Independent Expenditures: Spending to support/oppose candidates

list

List schedule f on OpenFEC (Federal Election Commission)

Coordinated Party Expenditures: Spending in coordination with candidates

list

List state election offices on OpenFEC (Federal Election Commission)

Get contact information for state election offices

search

Search candidates on OpenFEC (Federal Election Commission)

Search for candidates by name or other attributes

search

Search committees on OpenFEC (Federal Election Commission)

Search for committees by name or ID

Connect OpenFEC (Federal Election Commission) to Mastra AI via MCP

Follow these steps to wire OpenFEC (Federal Election Commission) into Mastra AI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

01

Install dependencies

Run npm install @mastra/core @mastra/mcp @ai-sdk/openai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save to agent.ts and run with npx tsx agent.ts
04

Explore tools

Mastra discovers 21 tools from OpenFEC (Federal Election Commission) via MCP

Why Use Mastra AI with the OpenFEC (Federal Election Commission) MCP Server

Mastra AI provides unique advantages when paired with OpenFEC (Federal Election Commission) through the Model Context Protocol.

01

Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure. add OpenFEC (Federal Election Commission) without touching business code

02

Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation

03

TypeScript-native: full type inference for every OpenFEC (Federal Election Commission) tool response with IDE autocomplete and compile-time checks

04

One-command deployment to any Node.js host. Vercel, Railway, Fly.io, or your own infrastructure

OpenFEC (Federal Election Commission) + Mastra AI Use Cases

Practical scenarios where Mastra AI combined with the OpenFEC (Federal Election Commission) MCP Server delivers measurable value.

01

Automated workflows: build multi-step agents that query OpenFEC (Federal Election Commission), process results, and trigger downstream actions in a typed pipeline

02

SaaS integrations: embed OpenFEC (Federal Election Commission) as a first-class tool in your product's AI features with Mastra's clean agent API

03

Background jobs: schedule Mastra agents to query OpenFEC (Federal Election Commission) on a cron and store results in your database automatically

04

Multi-agent systems: create specialist agents that collaborate using OpenFEC (Federal Election Commission) tools alongside other MCP servers

Example Prompts for OpenFEC (Federal Election Commission) in Mastra AI

Ready-to-use prompts you can give your Mastra AI agent to start working with OpenFEC (Federal Election Commission) immediately.

01

"List all presidential candidates for the 2024 election cycle."

02

"Show me the financial totals for candidate ID P00000001 in the 2024 cycle."

03

"Search for political committees with 'Action' in their name."

Troubleshooting OpenFEC (Federal Election Commission) MCP Server with Mastra AI

Common issues when connecting OpenFEC (Federal Election Commission) to Mastra AI through Vinkius, and how to resolve them.

01

createMCPClient not exported

Install: npm install @mastra/mcp

OpenFEC (Federal Election Commission) + Mastra AI FAQ

Common questions about integrating OpenFEC (Federal Election Commission) MCP Server with Mastra AI.

01

How does Mastra AI connect to MCP servers?

Create an MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.
02

Can Mastra agents use tools from multiple servers?

Yes. Pass multiple MCP clients to the agent constructor. Mastra merges all tool schemas and the agent can call any tool from any server.
03

Does Mastra support workflow orchestration?

Yes. Mastra has a built-in workflow engine that lets you chain MCP tool calls with branching logic, error handling, and parallel execution.

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