OmniRecall Beta: FAISS-Powered Memory Injection for Cloud LLM Chats

What OmniRecall Does
OmniRecall is a local mitmproxy bypass that intercepts traffic to cloud chat interfaces (tested on DeepSeek). It hacks into the proprietary SSE fragment stream and forces a long-term memory layer onto a system that was designed to be stateless.
Technical Mechanism
- Deep-Packet Parsing: Reconstructs the full assistant reply by tracking real-time patches
- Command Control: Detects [ADD], [UPDATE], [REMOVE], [CLEAR] from the AI's output
- Local Brain: Maintains memory.txt + FAISS index (sentence-transformers MiniLM-L6)
- Context Injection: Top recalled facts get force-fed into your next message as [RECALL: ...]
Current Status & Limitations
This is a beta/experimental release. The developer notes: "This is the closest I've gotten to the dream after weeks of debugging hell. It is buggy. It is experimental. [ADD] is mostly stable, but [SEARCH] is temperamental—if you want perfection, fix it yourself. I've hit my energy limit on this build."
Upstream UI changes will break it. The developer states: "If it breaks, that's on you now."
Requirements & Setup
Potato-PC Requirements:
- CPU only (faiss-cpu + all-MiniLM-L6-v2)
- No local LLM needed — augments the cloud models you already use
- Zero cost, zero API keys, 100% local data isolation
How to Deploy:
pip install mitmproxy faiss-cpu sentence-transformers numpyTrust the mitmproxy CA cert on your OS/browser (run mitmproxy once to generate it). Set system proxy to 127.0.0.1:8080. Then run:
mitmdump -s omnirecall.pyGo to chat.deepseek.com and start feeding it memories.
License Terms
The project uses an aggressively restrictive source-available license:
- No commercial use
- No private forks
- Mandatory public ALTERATIONS.md for any logic changes
- If you port to Claude/GPT-4o/whatever, keep it public per the license
The developer explains: "I've watched too many solo-dev projects get strip-mined, privatized, or turned into paid SaaS while the creator gets zero. This license isn't friendly—it's built to protect the work from exactly those people. If the terms scare you off, that's the point."
📖 Read the full source: r/LocalLLaMA
👀 See Also
Agentalmanac: A Catalog of 23 MCP Servers with Paste-Ready JSON Configs
Reddit user catalogues 23 MCP servers with paste-ready configs for Claude Desktop, Cursor, and Continue. Routes around archived servers to maintained alternatives. Hosted demo runs on Cloudflare Workers.

llmLibrarian: Local RAG Engine with MCP Integration for File-Based AI Search
llmLibrarian is a local RAG engine that exposes retrieval over MCP, allowing AI agents like Claude to query indexed files. It uses ChromaDB collections for organization, Ollama for synthesis, and keeps everything on-device.

cc-lens: Local Dashboard for Claude Code Session Analysis
A developer built cc-lens, a local-first dashboard that reads Claude Code session files from ~/.claude/ and provides usage analytics, cost tracking, and session replay. It runs entirely on your machine with no cloud sync, sign-ups, or telemetry.

Pair Programmer Plugin Adds Live Screen, Voice, and Audio Context to Claude Code
A developer has built a plugin called Pair Programmer that gives Claude Code real-time desktop perception by capturing screen, microphone, and system audio streams. The architecture uses specialized agents running in parallel for different input types, with indexing currently handled by cloud models but designed to be model-agnostic.