Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/cablate/memory-lancedb-mcp/claude-mdgit clone --depth 1 https://github.com/cablate/memory-lancedb-mcpWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.01019 | $0.01019 |
| Opus 5 | $0.00509 | $0.00509 |
| Sonnet 5 | $0.00204 | $0.00204 |
| Haiku 4.5 | $0.00102 | $0.00102 |
Grade A, and why
memory-lancedb-mcp CLAUDE.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
Project Principles
- Zero-config works —
EMBEDDING_API_KEYalone should give you a working memory server - Graceful degradation — Rerank API down? Fall back to cosine. FTS index fails? Fall back to lexical scan. No LLM? Skip extraction
- Behavior over implementation — Tests validate what the tool does, not how it's coded internally
- Backward compatible — New features must not break existing configs. Metadata schema changes must include migration
- Noise-resilient — Filter junk at every layer: input, extraction, retrieval, output
Git Workflow
- Never push directly to master. All changes go through feature branch → PR → CI pass → merge.
- Flow:
git checkout -b feat/xxx→git push -u origin feat/xxx→gh pr create - Release is fully automated: merge to master → auto version bump → npm publish → GitHub Release
Development Commands
npm run lint # ESLint
npm run format # Prettier auto-fix
npm run format:check # Prettier check (CI uses this)
npm run typecheck # TypeScript (currently has known errors, not enforced in CI)
npm test # All tests via node --test
Architecture
TypeScript executed directly via tsx/jiti — no build step.
Module Map
server.ts ← MCP entry point: tool registration + request routing
config.ts ← Config loading (env vars + JSON file → typed McpConfig)
bin/memory-lancedb-mcp.mjs ← CLI entry (tsx/jiti loader)
src/
├── store.ts ← LanceDB CRUD with scope filtering, serialized updates, FTS index
├── embedder.ts ← OpenAI-compatible embedding (LRU cache, multi-key rotation, auto-chunking)
├── retriever.ts ← Hybrid retrieval pipeline: vector+BM25 → RRF → rerank → scoring → filter
├── scopes.ts ← Multi-scope isolation (global, agent:, project:, user:, custom:)
├── decay-engine.ts ← Weibull decay scoring (recency × frequency × intrinsic × tier)
├── tier-manager.ts ← 3-tier lifecycle (Peripheral ↔ Working ↔ Core)
├── smart-metadata.ts ← L0/L1/L2 metadata layers, temporal versioning, relation graph
├── smart-extractor.ts ← LLM-powered extraction (standalone, not wired in server.ts by default)
├── noise-filter.ts ← Regex noise detection (denials, boilerplate, meta-questions)
├── access-tracker.ts ← Debounced access count tracking with reinforcement
├── llm-client.ts ← OpenAI chat wrapper for JSON extraction
├── chunker.ts ← Semantic text chunking for oversized inputs
├── memory-categories.ts ← 6-category taxonomy + dedup behavior rules
├── workspace-boundary.ts ← Routes profile/identity facts away from LanceDB
└── reflection-*.ts ← Reflection/governance stores (library code)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 90 lines · 1,019 tokens per session scan A 74d6eb149cbe
memory-lancedb-mcp CLAUDE.md is an instructions file published in the GitHub repository cablate/memory-lancedb-mcp (0 stars, last pushed 4mo ago), licensed MIT. It adds 1,019 tokens to every session, about $0.0051 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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