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RecallLattice

Python MCP License: MIT Version

A local-first permanent memory lattice for AI agents. RecallLattice combines SQLite, FTS5, ranked fuzzy recall, typed association graphs, spaced review, and a compact MCP interface without embeddings or a hosted database. Existing v3 installations retain the nigrty runtime/module names for complete compatibility.

Your database stays on your machine. The repository never needs it.

Why RecallLattice

  • Smarter recall: multi-keyword, stemming, prefix, typo-tolerant, tag-aware ranking.

  • Connected memory: new facts auto-link to related facts; recall can add one-hop graph context.

  • Low-token MCP: compact JSON emits each fact once and retrieves full text only on request.

  • Durable: WAL-mode SQLite, FTS synchronization triggers, integrity checks, and simple backups.

  • No vector stack: the core uses Python's standard library plus SQLite FTS5.

  • Full ownership: one portable database file and a localhost-only optional dashboard.

  • Backwards compatible: upgrades existing nigrty v3 databases in place without changing memory IDs.

Related MCP server: Synapto

Architecture

Hermes / any MCP client
        │ stdio
        ▼
  nigrty_mcp.py ───── compact ranked context
        │
        ▼
    nigrty.py ─────── dedup · scoring · decay · graph
        │
        ▼
  SQLite + FTS5 ───── memories · links · activity · XP
        ▲
        │
  FastAPI dashboard (optional, 127.0.0.1:8799)

Recall ranking

nigrty scores matches using:

  1. Exact phrase relevance.

  2. Exact token and stem matches.

  3. Prefix and typo-tolerant similarity.

  4. Tag matches and query coverage.

  5. Pin status, importance, and memory strength.

  6. Optional one-hop graph neighbors after direct results.

This keeps retrieval deterministic and inspectable while catching queries such as Qran reel vidio for a memory containing Quran Reels ... video.

Install

git clone https://github.com/Adam-ZS/RecallLattice.git
cd RecallLattice
./scripts/install.sh

The installer:

  • preserves an existing ~/.nigrty/nigrty.db;

  • backs up existing source files;

  • creates a persistent ~/.nigrty/.venv;

  • installs MCP and dashboard dependencies;

  • installs and starts the localhost dashboard service.

Open the dashboard at http://127.0.0.1:8799.

Hermes Agent integration

Add this MCP server to ~/.hermes/config.yaml through Hermes configuration tooling:

mcp_servers:
  nigrty:
    command: /home/YOU/.nigrty/.venv/bin/python
    args:
      - /home/YOU/.nigrty/nigrty_mcp.py
    enabled: true

For an existing nigrty entry, update its interpreter and enable it:

hermes config set mcp_servers.nigrty.command "$HOME/.nigrty/.venv/bin/python"
hermes config set mcp_servers.nigrty.enabled true

Start a new Hermes session after changing MCP configuration.

MCP tools

Tool

Purpose

nigrty_store

Store, categorize, tag, deduplicate, and auto-link a fact

nigrty_recall

Ranked compact recall with optional graph context

nigrty_get

Retrieve one full memory and its links

nigrty_forget

Delete one memory

nigrty_pin / nigrty_unpin

Control critical-memory priority

nigrty_review

Strengthen a memory through spaced review

nigrty_link

Add a typed graph edge

nigrty_stats

Inspect memory and graph health

nigrty_review_due

List memories needing review

nigrty_graph

Export graph nodes and edges

nigrty_heatmap

Summarize activity

nigrty_export

Export memory records

nigrty_prune

Preview stale low-value records before deletion

Compact versus full recall

Compact recall is the default:

{"query":"project memory","limit":8,"include_related":true,"max_chars":320}

Use "full": true only when the complete matching records are necessary. This progressive-disclosure pattern avoids paying for timestamps and bookkeeping on ordinary recalls.

Python API

import nigrty

saved = nigrty.store(
    "The project uses SQLite FTS5 for local ranked retrieval",
    category="project",
    importance=8,
)

matches = nigrty.recall("SQLite ranked project", limit=5)
print(matches[0]["content"])

Use a custom database path without changing source:

export NIGRTY_DB="$HOME/my-brain/memory.db"

Dashboard API

curl http://127.0.0.1:8799/api/stats
curl --get --data-urlencode 'q=ranked memory' http://127.0.0.1:8799/api/search
curl -X POST http://127.0.0.1:8799/api/store \
  -d 'content=One durable fact' -d 'importance=8'

The REST write endpoints use form encoding. The dashboard has no authentication and binds to localhost by default.

Backups and rollback

cp ~/.nigrty/nigrty.db ~/.nigrty/nigrty.db.backup-$(date +%Y%m%d)
./scripts/rollback-local.sh /path/to/pre-upgrade-backup

No migration deletes memories. v3.1 adds FTS maintenance triggers and an internal schema version, then rebuilds the search index from the canonical memories table.

Testing

python -m unittest discover -s tests -v
python -m py_compile nigrty.py nigrty_protocol.py nigrty_mcp.py server.py

The test suite covers deduplication, auto-linking, multi-keyword ranking, typo tolerance, tag filtering, access metadata, FTS store/update/delete synchronization, and compact output.

Privacy

Never commit nigrty.db, exports, backups, or .env files. The included .gitignore blocks these patterns, but inspect staged files before every push.

License

MIT — see LICENSE.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

No tool schema history has been recorded yet.

Maintenance

ActivityMaintained
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