FilingFirehose
@jaablon
About FilingFirehose
SEC EDGAR filings parsed and exposed via MCP — body-text-classified 8-Ks (7.3% of recent Item 8.01 filings have buried 1.05/5.02 events the filer didn't report), Schedule 13D/G with 21+ activist filers auto-tagged, S-3/424B5 ATM offering detection. Free public tier covers past 72
Basic information
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"filingfirehose": {
"url": "https://filingfirehose.com/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 FilingFirehose?
FilingFirehose is a Python client for the FilingFirehose SEC EDGAR API that delivers body-text–parsed 8-K filings with buried-event detection, activist-tagged Schedule 13D/G filings, and ATM offering data extracted from S‑3 / 424B5 prospectus supplements. It is built for financial analysts, quantitative researchers, and compliance teams who need structured, classified SEC data.
How to use FilingFirehose?
Install via pip install filing-firehose. Instantiate FilingFirehose() without an API key for the free tier (last 72 hours) or with an api_key for the full historical archive. Use methods such as recent_8k(), recent_13d(), and recent_atm() with optional filters.
More Productivity MCP servers
TickTick MCP Server
alexarevalo9A Model Context Protocol (MCP) server designed to integrate with the TickTick task management platform, enabling intelligent context-aware task operations and automation.
MCPControl
CheffromspaceMCP server for Windows OS automation
Openfate Bazi Mcp
openfate-aiOpenFate Bazi MCP server with deterministic Four Pillars calculation, True Solar Time, branch interactions, and reverse Bazi lookup.
Todo List MCP Server
RegiByteAn MCP server for managing todos within LLMs, created for educational purposes
ATLAS: Task Management System
cyanheadsA Model Context Protocol (MCP) server for ATLAS, a Neo4j-powered task management system for LLM Agents - implementing a three-tier architecture (Projects, Tasks, Knowledge) to manage complex workflows. Now with Deep Research.
Comments