inkwell-memory CLAUDE.md

inkwell-memory CLAUDE.md is an instructions file for coding agents from veronchenko/inkwell-memory. It costs 2,378 tokens per session, scanned A, original, MIT.

A persistent memory server for AI assistants that stores Markdown notes and builds searchable indexes from them. It supports keyword and meaning-based search, tags, typed entries, links between entries, and maintenance checks.

In plain words
What is it for?
Use it to remember information, search or recall notes, list and tag stored entries, remove memories, rebuild indexes, inspect linked knowledge, or run integrity checks.
Why use it?
It gives an AI assistant a structured place to save and retrieve information across conversations instead of relying only on the current chat.

Instructions file

Install

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.

agentmods
npx agentmods add instructions/veronchenko/inkwell-memory/claude-md
Clone the repo
git clone --depth 1 https://github.com/veronchenko/inkwell-memory

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for inkwell-memory CLAUDE.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/veronchenko/inkwell-memory/claude-md.svg)](https://agentmods.dev/instructions/veronchenko/inkwell-memory/claude-md)
Your own site
<a href="https://agentmods.dev/instructions/veronchenko/inkwell-memory/claude-md"><img src="https://agentmods.dev/badge/instructions/veronchenko/inkwell-memory/claude-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 2,378 This file is loaded in full into every session.
When invoked 2,378 The same file — it is already loaded in full.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.02378 $0.02378
Opus 5 $0.01189 $0.01189
Sonnet 5 $0.00476 $0.00476
Haiku 4.5 $0.00238 $0.00238

Measured 5d ago against content hash 2a5225049b1b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

inkwell-memory CLAUDE.md scanned grade A with 1 finding 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 5d ago.

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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- `src/cli.py` — `inkwell` console script (installed via `pyproject.toml`'s `[project.scripts]`, `pip install -e .` in the Dockerfile): thin `urllib`-based HTTP client to `admin_api` for `add-team`/`list-teams`/`revoke-t
CLAUDE.md · 46 lines

How it starts

The opening of the file, as written. The whole thing — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CLAUDE.md — inkwell_memory

MCP server providing persistent memory for AI agents. Markdown files are the source of truth; a hybrid SQLite FTS5 + semantic embedding index (fused via Reciprocal Rank Fusion) provides search, plus graph-style relations (kb://uuid#type links).

Layout

  • src/server.py — MCP tool definitions (remember, recall, search, list, tags, forget, rebuild, doctor)
  • src/schema.json + src/schema.py — the entry taxonomy as data: per-type required/body/membership/usage_boost/digest_on_recall. Loader resolves <data-path>/schema.json → packaged default, full replacement, never a merge; builds the entry_type enum injected into server.py's module globals before tool registration (PEP 563 annotations resolve there), so an undeclared type is rejected client-side. Read once at startup → editing it requires a restart.
  • src/doctor.py — schema-driven integrity pass (run_doctor), shared by the doctor tool, rebuild's warnings, and remember's conformance warnings via check_entry. Reads the Markdown files, not the index.
  • src/database.py — entry storage: Markdown + YAML frontmatter CRUD, UUID assignment
  • src/search_backend.pySQLiteBackend (index, unindex, search, rebuild, get_relations, get_all_relations) + kb:// relation extraction. search fuses BM25 (FTS5) with cosine similarity over local Model2Vec embeddings (_bm25_search + _vector_search + _rrf_fuse); embeddings are stored as a BLOB column on entries and computed lazily/in batch by the same code path that writes the row.
  • src/dashboard/ — web dashboard: FastAPI app (app.py, create_app(kb)) exposing REST CRUD + /api/graph over the same KnowledgeBase/SQLiteBackend the MCP tools use (no protocol duplication), a single static index.html (vanilla JS force-directed canvas graph, no build step/CDN) served at /, and __main__.py as its own uvicorn entry point (INKWELL_DASHBOARD_HOST/INKWELL_DASHBOARD_PORT, default port 8193). Runs as a second process in the same container via docker-entrypoint.sh, alongside server.py's MCP process. Single-KnowledgeBase only — not yet multi-tenant-aware (see below).
  • src/team_admin.pyTeamAdminStore: SQLite registry (<data_path>/admin.db) mapping a team name to its data folder (<data_path>/teams/<name>/) and a SHA-256-hashed API key. Only touched in multi-tenant mode.
  • src/admin_api/ — loopback-only FastAPI app (app.py, create_app(store, api_key)) for add-team/list-teams/revoke-team, guarded by INKWELL_ADMIN_API_KEY; __main__.py is its own uvicorn entry point (INKWELL_ADMIN_API_HOST/INKWELL_ADMIN_API_PORT, default port 8194, not proxied/exposed). Third process in the container, started only when INKWELL_MULTI_TENANT=1.
  • src/cli.pyinkwell console script (installed via pyproject.toml's [project.scripts], pip install -e . in the Dockerfile): thin urllib-based HTTP client to admin_api for add-team/list-teams/revoke-team, plus a backup subcommand (on-demand tar.gz of teams//admin.db to a given --dest, no rotation/schedule built in). Run via docker exec <container> inkwell <command>; reads INKWELL_ADMIN_API_URL/INKWELL_ADMIN_API_KEY from the same container environment the admin API itself uses.
  • tests/ — mirrors src/ (test_server.py, test_database.py, test_backends.py, test_dashboard.py)

Read the full file on GitHub · 46 lines

Changes

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.

  1. 5d ago First seen · 46 lines · 2,378 tokens per session scan A 2a5225049b1b

Subscribe to this mod's changes

inkwell-memory CLAUDE.md is an instructions file published in the GitHub repository veronchenko/inkwell-memory (2 stars, last pushed 22d ago), licensed MIT. It adds 2,378 tokens to every session, about $0.0119 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.