Valuein MCP Server - US SEC Financial Data

Name: Valuein MCP Server - US SEC Financial Data
Author: valuein

@valuein

Repository

About Valuein MCP Server - US SEC Financial Data

Institutional-grade SEC financial data for AI agents — in one line of config.

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "valuein-sec-edgar": {
      "type": "http",
      "url": "https://mcp.valuein.biz/mcp"
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Valuein MCP Server - US SEC Financial Data?

Valuein MCP Server - US SEC Financial Data is an MCP server that provides AI agents with institutional-grade access to 35 years of SEC EDGAR financial data covering 16,000+ US public companies and 100M+ financial facts. It is designed for analysts, portfolio managers, quants, developers, and financial content creators who need to query fundamentals, ratios, filings, and run backtests directly from their AI assistant.

How to use Valuein MCP Server - US SEC Financial Data?

Configure your MCP-compatible client (e.g., Claude, Cursor, ChatGPT, Codex) with the server URL https://mcp.valuein.biz/mcp and a Bearer token obtained from a subscription. Once connected, use any of the 15 built-in tools or 8 analyst/quant playbooks to look up companies, pull financial statements, compare peers, screen markets, or run survivorship-free backtests.

Key features of Valuein MCP Server - US SEC Financial Data

Look up any US public company by ticker or CIK
Pull income statement, balance sheet, and cash flow data
Read financial ratios such as margins, ROIC, and leverage
Compare fundamentals side-by-side with selected peers
Link directly to SEC EDGAR source filings (10-K, 10-Q, 8-K)
Screen the market with factor filters and quality signals

Use cases of Valuein MCP Server - US SEC Financial Data

Analysts and PMs run earnings reviews, forensic tear-downs, and peer benchmarking without leaving their AI assistant
Quants build point-in-time factor models and survivorship-free backtests
Developers ship

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