rei-memory-mcp
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@rei-memory-mcpfind theories that mention decision fatigue, tier hypothesis"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
rei-memory-mcp
Read-only MCP server that lets Rei / Claude query the Rei-AIOS SEED_KERNEL (1,677+ theories as of 2026-08-19) by full-text search, ID, or STEP.
Phase 1 — read only. No write path is exposed as an MCP tool. Ingestion is a one-shot script; theory additions and promotions belong to Phase 2 (seed_propose staging table).
Design principle
The three-tier taxonomy (proven / hypothesis / speculative) is a required schema field. A theory without a tier cannot be ingested. The epidemic-hygiene discipline is enforced by the schema, not by human attention.
Related MCP server: Ek-Chuah MCP
Tools
Tool | Purpose |
| FTS5 full-text over title+body. Trigram tokenizer for Japanese. |
| Full body + fan-out links ( |
| Per-STEP count + tier distribution. Only ~3% of current SEED_KERNEL rows carry a STEP marker; the rest fall under the |
Setup
Python 3.11+ and SQLite 3.34+ (for FTS5 trigram tokenizer — bundled with Python 3.11+).
# from repo root
python -m venv .venv
.venv/Scripts/activate # Windows
source .venv/bin/activate # Unix
pip install -e '.[dev]'Building the database
The SEED_KERNEL lives as TypeScript source in rei-aios/src/axiom-os/seed-kernel*.ts. Dump it to JSONL, then ingest:
# 1. dump (run inside the rei-aios repo; script is bundled there)
cd path/to/rei-aios
npx tsx scripts/dump-seed-kernel-json.ts > /path/to/rei-memory-mcp/data/seed-kernel-dump.jsonl
# 2. ingest into SQLite
cd path/to/rei-memory-mcp
python scripts/ingest.py \
--input data/seed-kernel-dump.jsonl \
--db data/seed_kernel.dbBoth data/*.jsonl and data/*.db are gitignored — regenerate as needed.
Running the MCP server
# stdio transport (default)
python -m rei_memory_mcp.server
# or via console script:
rei-memory-mcpThe DB path is picked from REI_MEMORY_DB (default: ./data/seed_kernel.db).
Claude Desktop configuration
Add to your Claude Desktop MCP settings (adjust paths):
{
"mcpServers": {
"rei-memory": {
"command": "python",
"args": ["-m", "rei_memory_mcp.server"],
"cwd": "C:/Users/user/rei-memory-mcp",
"env": {
"REI_MEMORY_DB": "C:/Users/user/rei-memory-mcp/data/seed_kernel.db"
}
}
}
}Tests
pytestThe test on Japanese queries (test_search.py::test_japanese_query_hits) is the load-bearing signal — if that fails, the trigram tokenizer is broken and search is silently useless.
Honest scope
Read-only. No write MCP tool exists on purpose. Wrong memories should not have a fast path to form.
Trigram Japanese. Queries of 2 characters or shorter will not match Japanese text (that is how the trigram tokenizer works). Use 3+ character queries.
STEP coverage. Only ~3% of current SEED_KERNEL entries embed a
STEP Nmarker in their body text.seed_list_stepsfaithfully reports this.id shape. The current SEED_KERNEL mixes three ID patterns (
T-\d+,invented-*, kebab-case slug). All three are accepted; no reshaping.No vector search. FTS5 trigram is the whole retrieval story in Phase 1. If it turns out to be insufficient, Phase 2 can add embeddings alongside — not replace.
Roadmap (not implemented)
Phase 2 —
seed_proposestaging table + human approval → promotion intotheories. Direct writes totheorieswill not be exposed as a tool.Phase 3 — promotion history table so the arc of a theory (hypothesis → proven) is itself an artifact.
Phase 4 — access-count decay for ranking.
immutable: truerows are exempt; nothing is ever deleted.
License
AGPL-3.0 (with commercial dual-license terms — see LICENSE). Matches the rei-aios main repository.
急がず、ゆっくりと。種は育ちます。
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Maintenance
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