Equibles: Self-Hosted MCP Server for U.S. Financial Data – SEC Filings, 13F, Insider Trades, FRED

Running local models as agents often means lacking current, real-world data. Equibles is a self-hosted, open-source MCP server that fills that gap by scraping and serving public U.S. financial data directly to MCP-capable clients — no cloud dependency, no API keys, no telemetry.
What It Serves
- SEC filings (10-K, 10-Q, 8-K) with full-text search
- 13F institutional holdings and insider trades (Form 3/4)
- Congressional trades
- FINRA short volume / short interest
- SEC fails-to-deliver
- FRED economic indicators
- CFTC futures positioning
- CBOE VIX and put-call ratios
- Daily prices + technical indicators
The data is exposed as MCP tools, so any MCP-capable client (Claude Code, Claude Desktop, Cursor, or your own local-model agent loop) can query it directly. Everything runs on your machine.
Getting Started
Clone the repo and follow the setup instructions:
git clone https://github.com/daniel3303/Equibles cd Equibles # Follow README for configuration and running
No API keys needed — it scrapes public sources. Ideal for developers who want to give their local LLM agents real-time financial data without sending queries to third-party APIs.
📖 Read the full source: r/LocalLLaMA
👀 See Also

Open-source MCP suite improves Claude Code generation quality by 15-20%
An open-source MCP suite consisting of three local servers and a prompt skill addresses the 'bad token' problem in AI code generation, with one customer reporting 15-20% quality improvement for Claude Code.

Semble: Code Search for AI Agents Using 98% Fewer Tokens Than grep+read
Semble is an open-source code search library for AI agents that combines static Model2Vec embeddings with BM25, running entirely on CPU. It indexes a repo in ~250ms and answers queries in ~1.5ms, achieving 0.854 NDCG@10 — 99% of a 137M-parameter transformer's quality — while using 98% fewer tokens than grep+read.

A Pattern for Running Claude Code on Overnight Unattended Sessions Without Drift
A three-piece framework — chain runner, supervisor, and a single handoff contract — solves the feedback-loop drift problem in multi-hour autonomous Claude Code sessions.

Open-Source JARVIS Desktop Assistant Built with Claude Code in 2 Days
A developer built a macOS desktop AI assistant called JARVIS in 1-2 days using Claude Code as the primary development tool. The application features a holographic UI, 18 native tools for system control, voice interface, and integrations with Gmail, Google Calendar, Notion, GitHub, and Obsidian.