totalreclaw
End-to-end encrypted memory + knowledge graph for AI agents.
Store, search, and recall memories across any AI agent with zero-knowledge encryption. Your data is encrypted on-device before it leaves -- the server never sees plaintext.
As of 2.4.6, the client uses Memory Taxonomy v1 (6 canonical types: claim | preference | directive | commitment | episode | summary) and Retrieval v2 Tier 1 source-weighted reranking (user-sourced facts rank higher than assistant-sourced facts on tied BM25 + cosine scores). See the memory types guide. Existing pre-v1 vault entries decrypt transparently.
Features
- End-to-end encrypted -- XChaCha20-Poly1305 encryption, HKDF key derivation from a BIP-39 recovery phrase
- Portable -- Same recovery phrase works across Hermes, OpenClaw, Claude Desktop, IronClaw, ZeroClaw
- Memory Taxonomy v1 -- 6 speech-act types + required provenance (
user | user-inferred | assistant | external | derived) and 8 life-domain scopes. v1 is the only write path (no env-var gating). - Retrieval v2 Tier 1 -- source-weighted reranking via
totalreclaw-core@2.5.5PyO3 bindings (user-sourced facts rank higher on tied scores) - G-pipeline extraction -- merged-topic prompt, provenance filter (lax), comparative rescoring, volatility heuristic
- Local embeddings -- Harrier-OSS-v1-270M runs on-device (no API calls)
- Hybrid search -- BM25 + cosine similarity + RRF reranking
- LSH bucketing -- Locality-sensitive hashing for encrypted search
- On-chain storage -- Managed service stores on Gnosis mainnet (single chain, all tiers) via ERC-4337; outer protobuf v4
Quick Start
pip install totalreclaw
import asyncio
from totalreclaw import TotalReclaw
async def main():
client = TotalReclaw(
recovery_phrase="your twelve word recovery phrase here",
server_url="https://api.totalreclaw.xyz", # default, can be omitted
)
# REQUIRED: resolve Smart Account address and register with relay
await client.resolve_address()
await client.register()
# Store a memory — v1 taxonomy defaults: type="claim", source="user", scope="unspecified".
# Importance is 1-10 (int) or 0-1 (float, auto-normalized).
# v1 types: claim | preference | directive | commitment | episode | summary
# scope, volatility, reasoning also accepted.
fact_id = await client.remember(
"Pedro prefers dark mode for all editors",
fact_type="preference",
scope="personal",
importance=8,
)
# Search memories
results = await client.recall("What does Pedro prefer?")
for r in results:
print(f" [{r.rrf_score:.3f}] {r.text}")
# Delete a memory
await client.forget(fact_id)
# Export all memories
facts = await client.export_all()
# Check billing
status = await client.status()
print(f"Tier: {status.tier}, Used: {status.free_writes_used}/{status.free_writes_limit}")
await client.close()
asyncio.run(main())
Important: You must call resolve_address() and register() before any operations. resolve_address() derives the CREATE2 Smart Account address via an RPC call, and register() authenticates with the relay.
With Embeddings (Recommended)
For semantic search, install with embedding support:
pip install totalreclaw
from totalreclaw import TotalReclaw
from totalreclaw.embedding import get_embedding
client = TotalReclaw(recovery_phrase="...")
# Store with embedding for semantic search
text = "Pedro prefers dark mode"
embedding = get_embedding(text)
await client.remember(text, embedding=embedding)
# Search with embedding
query = "What are Pedro's UI preferences?"
query_emb = get_embedding(query)
results = await client.recall(query, query_embedding=query_emb)
The embedding model (~600 MB) downloads automatically on first use.
Hermes Agent Plugin
pip install totalreclaw[hermes]
The plugin registers automatically with Hermes Agent v0.5.0+. See the Hermes setup guide.
Architecture
Plaintext → XChaCha20-Poly1305 encrypt → Blind indices (SHA-256) → LSH buckets → On-chain via relay
↓
Query → Blind trapdoors → GraphQL search → Decrypt candidates → BM25+Cosine+RRF rerank → Top 8
All encryption happens client-side. The relay server and on-chain storage never see plaintext.
Cross-Language Parity
This Python client produces byte-for-byte identical outputs to the TypeScript implementation (@totalreclaw/mcp-server):
- Key derivation (HKDF-SHA256)
- XChaCha20-Poly1305 wire format (nonce || tag || ciphertext)
- Blind indices (SHA-256 + Porter stemming)
- Content fingerprints (HMAC-SHA256)
- LSH bucket hashes (32-bit x 20 tables)
Memories stored by the Python client can be recalled by the MCP server, and vice versa.
Learn More
- Client setup guide (v1)
- Memory types guide
- v1 migration guide
- Environment variables
- Hermes setup guide
- Feature comparison
Changelog
The latest changes live in CHANGELOG-public.md — kept current there rather than duplicated in this README.
License
MIT
1 maintainer
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