The memory your AI should have had from the start. Automatic capture, automatic recall, 100% local. One SQLite file, zero cloud. Works with Claude Code, Claude CLI, Cursor, Codex CLI, Gemini CLI.
# Add to your Claude Code skills
git clone https://github.com/buildingjoshbetter/TrueMemoryLast scanned: 6/7/2026
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}TrueMemory is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by buildingjoshbetter. The memory your AI should have had from the start. Automatic capture, automatic recall, 100% local. One SQLite file, zero cloud. Works with Claude Code, Claude CLI, Cursor, Codex CLI, Gemini CLI. It has 368 GitHub stars.
Yes. TrueMemory passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/buildingjoshbetter/TrueMemory" and add it to your Claude Code skills directory (see the Installation section above).
TrueMemory is primarily written in Python. It is open-source under buildingjoshbetter on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh TrueMemory against similar tools.
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It finds signal in the noise. Your AI sees thousands of messages. TrueMemory figures out which ones actually matter and throws away the rest. No manual tagging, no prompt engineering. It just knows.
It gets sharper over time. It's not a static database. It's a living memory that grows with you. It resolves contradictions when you change your mind, updates stale facts, and consolidates what it knows. The longer you use it, the better it gets.
It works without you thinking about it. TrueMemory automatically captures memories from your conversations and automatically injects the right ones into your next session. You never have to store or search for anything manually. It just happens.
It's 100% local. One SQLite file on your machine. Your memories never leave your device. No cloud, no API keys needed. Your data is yours. (Anonymous usage telemetry is the only exception — never memory content — and one env var turns it off. Details.)
Without TrueMemory: "What framework are we using?" Asked for the 12th time this week. Your agent starts every session with amnesia. It doesn't know your name, your stack, or anything you told it yesterday.
With TrueMemory: Your agent already knows you use FastAPI, prefer Pydantic v2, and that your auth middleware lives in
src/auth/. It remembers your corrections, your preferences, and your decisions. Across every session, forever.
| System | LoCoMo | LongMemEval | Local-first | Auto-capture | License |
|---|---|---|---|---|---|
| TrueMemory Pro | 93.0% | 92.0% | ✅ | ✅ | AGPL-3.0 |
| TrueMemory Base | 92.0% | 84.1% | ✅ | ✅ | AGPL-3.0 |
| Mem0 | 61.4% | — | Partial | ❌ | Apache-2.0 |
| Supermemory | 65.4% | — | ❌ | ❌ | Cloud API |
| MemOS | 75.8% | — | ✅ | ❌ | Apache-2.0 |
| ReadAgent | 79.5% | — | ❌ | ❌ | Research |
All benchmarks independently reproducible. Scripts included in
benchmarks/.
curl -LsSf https://raw.githubusercontent.com/buildingjoshbetter/TrueMemory/main/install.sh | sh
Installs everything in an isolated environment. Downloads ~1.5GB of AI models. No data leaves your machine. No sudo required.
Cmd + Space, type Terminal. Linux: Ctrl + Alt + T. Windows: open PowerShell.Cmd+Q).Windows (PowerShell):
irm https://raw.githubusercontent.com/buildingjoshbetter/TrueMemory/main/install.ps1 | iex
That's it. TrueMemory remembers your conversations automatically from here. Need help? Join our Discord.
If TrueMemory saves you time, a ⭐ helps other devs find it.
pip install truememory
from truememory import Memory
m = Memory()
m.add("Prefers dark mode and TypeScript", user_id="alex")
print(m.search("preferences", user_id="alex"))
Same architecture, three tiers. All included in a single install. Switch anytime by saying "switch to Pro" or "switch to Base."
| Edge | Base | Pro | |
|---|---|---|---|
| LoCoMo | 89.6% | 92.0% | 93.0% |
| LongMemEval | — | — | 92.0% |
| BEAM-1M | — | — | 76.6% (SOTA) |
| Embedding model | 8 MB lightweight | 600 MB high-accuracy | 600 MB high-accuracy |
| Reranker | 22M params | 149M params | 149M params |
| HyDE search | — | — | ✅ (requires LLM API key) |
| Runs on | Any machine, CPU only | 4 GB+ RAM | 4 GB+ RAM + API key |
Edge works everywhere. Base is the strongest fully-offline tier. Pro adds AI-powered query expansion for the highest scores.
Tested across three major benchmarks with all systems sharing the same answer model (GPT-4.1-mini), judge (GPT-4o-mini, 3x majority vote), and scoring pipeline.
| Benchmark | What it tests | TrueMemory Pro |
|---|---|---|
| LoCoMo | 1,540 questions across 10 conversations | 93.0% |
| LongMemEval | 500 multi-session questions | 92.0% |
| BEAM-1M | 700 questions at 1M+ tokens | 76.6% (SOTA) |
| BEAM-10M | 200 questions at 10M tokens | 65.0% |
Every benchmark script is self-contained and runs on Modal.
All benchmarks use the same eval pipeline. Nothing is hidden. Full details: LoCoMo | LongMemEval | BEAM
Lifecycle hooks capture conversations automatically. No manual work needed. Your memories stay local in a single SQLite file.
from truememory import Memory
m = Memory()
m.add("Prefers dark mode and TypeScript", user_id="alex")
m.add("Works at Anthropic as a senior engineer", user_id="alex")
m.add("Always sign commits with GPG", directive=True) # directives auto-load every session
results = m.search("What are Alex's preferences?", user_id="alex")
results = m.search_deep("career history?", user_id="alex") # multi-round, higher accuracy
| Method | Description |
|---|---|
m.add(content, user_id) |
Store a memory (directive=True for standing instructions that auto-load at the start of every session) |
m.search(query, user_id) |
Search (6-layer pipeline + reranker) |
m.search_deep(query, user_id) |
Multi-round agentic search |
m.get(id) / m.get_all(user_id) |
Retrieve memories |
m.update(id, content) / m.delete(id) |
Modify or remove |
m.stats() |
System statistics |
| Getting Started | Install to first memory |
| Python API Reference | Full Memory class reference |
| MCP Tool Reference | All 11 MCP tools |
| CLI Reference | truememory-mcp and truememory-ingest |
| Environment Variables | All TRUEMEMORY_* config options |
| Architecture Deep Dive | 6-layer retrieval pipeline, encoding gate |
| Tier Selection Guide | Edge vs Base vs Pro |
| Debugging | Logs, traces, common issues |