Total Recall: Local Knowledge Graph for Claude Code Conversation History
What Total Recall Does
Total Recall solves the problem of re-explaining decisions across Claude Code sessions by making conversation history searchable. Claude Code stores conversations as JSONL files in ~/.claude/projects/, with each line containing a message object (role, content, timestamps, ID, parentUuid). These parent references form a Directed Acyclic Graph (DAG) because conversations branch with tool calls and interruptions.
Technical Implementation
The system ingests JSONL transcripts into a SQLite database with:
- Full-text search
- Vector embeddings using local Ollama (no cloud) with nomic-embed-text
- Semantic cross-linking
- DAG-aware retrieval that walks parent chains backward from search hits
- Project-based session tagging
When you ask a question like "What was that restaurant with the great chile rellenos?", Claude queries the database and returns actual conversation excerpts with surrounding context, not summaries.
Additional Features
- A "where were we" script shows the last 20 messages from the most recent session
- ChatGPT importer that authenticates via Playwright and calls the backend API to pull full conversation trees with timestamps, model metadata, DALL-E images, and code interpreter outputs
- Auto-ingests every 15 minutes
- Everything is local - one file you can copy to another machine
Current Deployment
The creator's deployment handles:
- 28K chunks
- 63K semantic links
- 255 MB storage
- 49 sessions across 6 projects
Open Source Availability
The repository at https://github.com/aguywithcode/total-recall contains:
- Full pipeline (ingest, embed, link, retrieve, browse)
- ChatGPT scraper
- Setup instructions
- CLAUDE.md integration guide
- Background documentation with the full build story
📖 Read the full source: r/ClaudeAI
👀 See Also
Benchmark Shows CLI Tool Reduces Claude Code Token Costs by 32% Through Structural Navigation
A developer built a Rust CLI tool that gives Claude Code agents structural navigation commands like 'show me a 180-token summary of this 6,000-token class.' Benchmarking on Sonnet 4.6 across 54 automated runs showed 32% lower cost per task and 67% more code edits per session.
Colony: A Local-First Coordination Layer That Cuts Multi-Agent Handoff Tokens from 30K to 400
Colony is a local-first coordination substrate that reduces multi-agent handoff costs from ~30,000 tokens to ~400 by replacing context replay with compact observations stored in SQLite.
AI Agent Session Center: 3D Dashboard for Monitoring Claude Code Sessions
AI Agent Session Center is a real-time dashboard that visualizes Claude Code sessions as 3D robots in a cyberdrome, with animations showing agent status and features including live terminal views, approval alerts, and session resume. It installs via npx with lightweight bash hooks.
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