2,500+ MCP servers ready to use
Vinkius

SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison MCP Server for Mastra AI 4 tools — connect in under 2 minutes

Built by Vinkius GDPR 4 Tools SDK

Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison through the Vinkius and Mastra agents discover all tools automatically — type-safe, streaming-ready, and deployable anywhere Node.js runs.

Vinkius supports streamable HTTP and SSE.

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: {
      "sec-edgar-financials-revenue-income-assets-eps-industry-comparison": {
        url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
      },
    },
  });

  const tools = await mcpClient.getTools();
  const agent = new Agent({
    name: "SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison Agent",
    instructions:
      "You help users interact with SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison " +
      "using 4 tools.",
    model: openai("gpt-4o"),
    tools,
  });

  const result = await agent.generate(
    "What can I do with SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison?"
  );
  console.log(result.text);
}

main();
SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison
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 SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison MCP Server

SEC XBRL financial data.

Mastra's agent abstraction provides a clean separation between LLM logic and SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison tool infrastructure. Connect 4 tools through the 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.

4 Tools

  • Key Financials — Revenue, income, assets, EPS, cash
  • Financial Metric — Any US-GAAP concept
  • All Facts — Complete XBRL data dump
  • Industry Comparison — Cross-company metric frames

Zero Auth

Like a free Bloomberg terminal

The SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison MCP Server exposes 4 tools through the Vinkius. Connect it to Mastra AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison to Mastra AI via MCP

Follow these steps to integrate the SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison MCP Server with Mastra AI.

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 4 tools from SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison via MCP

Why Use Mastra AI with the SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison MCP Server

Mastra AI provides unique advantages when paired with SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison through the Model Context Protocol.

01

Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure — add SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison 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 SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison 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

SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison + Mastra AI Use Cases

Practical scenarios where Mastra AI combined with the SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison MCP Server delivers measurable value.

01

Automated workflows: build multi-step agents that query SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison, process results, and trigger downstream actions in a typed pipeline

02

SaaS integrations: embed SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison 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 SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison on a cron and store results in your database automatically

04

Multi-agent systems: create specialist agents that collaborate using SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison tools alongside other MCP servers

SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison MCP Tools for Mastra AI (4)

These 4 tools become available when you connect SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison to Mastra AI via MCP:

01

get_all_company_facts

This is the raw, comprehensive dataset — hundreds of concepts across multiple years. Use get_key_financials for a curated summary, or this for deep analysis. Get ALL XBRL financial facts for a company — complete financial data dump

02

get_financial_metric

Common concepts: Revenues, NetIncomeLoss, Assets, Liabilities, StockholdersEquity, EarningsPerShareBasic, LongTermDebt, ResearchAndDevelopmentExpense, CashAndCashEquivalentsAtCarryingValue, CommonStockSharesOutstanding. If the concept is not found, returns available concepts. Get a specific US-GAAP financial concept for a company (e.g., Revenue, Debt, R&D)

03

get_industry_comparison

Useful for industry comparison and screening. Example: get all companies' Revenue for CY2024. Period format: CY2024 (annual), CY2024Q1 (quarterly), CY2024Q1I (instant). Compare a financial metric across ALL companies — industry-wide XBRL frame data

04

get_key_financials

Returns the most recent 5 reported values across 10-K and 10-Q filings. This is like a mini Bloomberg terminal — for free. Get key financial data for a company — revenue, net income, assets, equity, EPS, cash

Example Prompts for SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison in Mastra AI

Ready-to-use prompts you can give your Mastra AI agent to start working with SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison immediately.

01

"Get Apple's key financial data — revenue, income, assets, and EPS"

02

"What is Meta's exact Research and Development Expense?"

03

"Show me a comparison of Revenue across all companies for CY2024"

Troubleshooting SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison MCP Server with Mastra AI

Common issues when connecting SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison to Mastra AI through the Vinkius, and how to resolve them.

01

createMCPClient not exported

Install: npm install @mastra/mcp

SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison + Mastra AI FAQ

Common questions about integrating SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison 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.

Connect SEC EDGAR Financials — Revenue, Income, Assets, EPS & Industry Comparison to Mastra AI

Get your token, paste the configuration, and start using 4 tools in under 2 minutes. No API key management needed.