@ghostpaw/codex

@ghostpaw/codex

Local, evidence-backed memory for AI agents. One SQLite file, zero runtime dependencies.

Codex stores what an agent believes as claims with a source, a certainty, evidence counts, decay and an honest revision history. Agents search before they remember, confirm or correct instead of appending, and see which beliefs are stale, fading or weakly evidenced. It runs as a TypeScript library, an MCP server, a CLI and an Agent Skill, all generated from the same seven tools.

Website: ghostpaw.dev/agent-memory

Requires Node.js 24+ (uses the built-in node:sqlite).

30-second quickstart

MCP server

Every client below starts the same stdio server: npx -y @ghostpaw/codex mcp. Beliefs live in ~/.ghostpaw/codex.db unless the GHOSTPAW_CODEX_DB environment variable (absolute path) or --db <path> says otherwise.

Claude Code

claude mcp add ghostpaw-codex -- npx -y @ghostpaw/codex mcp

or as a plugin, which also installs the skill:

/plugin marketplace add GhostPawJS/codex
/plugin install ghostpaw-codex@ghostpaw-codex

Codex CLI (~/.codex/config.toml)

[mcp_servers.ghostpaw-codex]
command = "npx"
args = ["-y", "@ghostpaw/codex", "mcp"]

Cursor (.cursor/mcp.json), Claude Desktop (claude_desktop_config.json) or a project .mcp.json:

{
  "mcpServers": {
    "ghostpaw-codex": {
      "command": "npx",
      "args": ["-y", "@ghostpaw/codex", "mcp"]
    }
  }
}

Claude Desktop users can also install server.mcpb from the latest GitHub release. A Dockerfile is included for container hosts: docker build -t ghostpaw-codex . && docker run -i --rm -v codex:/data ghostpaw-codex.

The server speaks MCP 2026-07-28 (stateless, server/discover) and the initialize-based revisions 2025-11-25, 2025-06-18, 2025-03-26 and 2024-11-05.

CLI

npx -y @ghostpaw/codex remember_belief --claim "Deploys go out on Tuesdays" --source explicit --category procedure
npx -y @ghostpaw/codex search_codex --query "when do we deploy"
npx -y @ghostpaw/codex tools              # list tools
npx -y @ghostpaw/codex describe revise_belief

Install globally for the ghostpaw-codex binary: npm i -g @ghostpaw/codex. ghostpaw-codex mcp starts the stdio server.

Agent Skill

SKILL.md (repo root) and skills/codex/SKILL.md follow the Agent Skills format and ship in the npm package. Copy skills/codex/ into your agent's skills folder, or print it:

npx -y @ghostpaw/codex skill > SKILL.md

Library

npm install @ghostpaw/codex

import { DatabaseSync } from 'node:sqlite';
import { initCodexTables, read, write } from '@ghostpaw/codex';

const db = new DatabaseSync('codex.db');
initCodexTables(db);

const { id } = write.remember(db, {
  claim: 'The API uses GraphQL with a REST fallback.',
  source: 'explicit',
  category: 'fact',
});
write.confirmBelief(db, id);
write.correctBelief(db, id, {
  claim: 'The API uses GraphQL exclusively; REST was retired.',
  source: 'observed',
  category: 'fact',
});

read.recall(db, 'graphql api'); // ranked, lineage-aware
read.listFlags(db);             // stale, fading, low-trust, single-evidence

Wire the same tools into any LLM SDK. Each tool carries a JSON Schema:

import { tools } from '@ghostpaw/codex';

for (const tool of tools.codexTools) {
  // tool.name, tool.description, tool.inputSchema, tool.handler(db, input)
}

Or embed the MCP server in your own process:

import { createCodexMcpServer } from '@ghostpaw/codex/mcp';
const server = createCodexMcpServer({ dbPath: './codex.db' });

Why not MEMORY.md?

A markdown memory file works until it doesn't:

• It only grows. Agents append, rarely delete, and the file ends up in every prompt. Codex returns the few beliefs that match a query (FTS5 plus local embeddings, fused by rank).
• Contradictions pile up. "We use REST" and "REST was retired" sit side by side. Codex detects near-duplicates on every write, and corrections supersede the old belief while keeping the lineage.
• Everything looks equally true. A guess and a confirmed fact read the same in prose. Codex tracks source (explicit, observed, distilled, inferred), certainty and evidence count, and flags what is stale or weakly supported.
• No time. Codex decays freshness, so old beliefs surface for review instead of quietly steering behaviour.
• Concurrent edits. Two agents writing one file clobber each other. Codex is a SQLite database in WAL mode.

It stays local: one file you can copy, back up or inspect with any SQLite tool. No server, no API key, no network.

Tools

Tool	What it does
search_codex	Hybrid lexical and semantic recall across active beliefs
review_codex	Dashboards: flags, status, trends, log
inspect_codex_item	One belief in full: metrics, lineage, nearby beliefs
remember_belief	Capture a claim with source, category and provenance
revise_belief	Confirm, correct, forget, defer or merge
retire_belief	Hard-delete for privacy or cleanup
dismiss_proximity	Mark two nearby beliefs as intentionally distinct

Results are structured (outcome: success | no_op | needs_clarification | error) with entities, next-step hints and recovery advice. The MCP server, CLI, SKILL.md and plugin manifests are generated from this registry (npm run surfaces) and drift-checked in CI.

Performance

Measured with npm run bench on Node 24.14.0, Linux, Intel Xeon (shared cloud vCPU), 10,000 beliefs in a file-backed database:

Operation	p50	p95
search_codex (tool)	3.6 ms	5.0 ms
MCP tools/call search, stdio framing included	3.8 ms	4.2 ms
read.recall	3.7 ms	4.8 ms
inspect_codex_item	3.5 ms	3.8 ms
write.remember (includes proximity scan)	4.5 ms	5.6 ms
review_codex	11.7 ms	13.2 ms

Cold start (process spawn to first response, median): --version 26 ms, MCP server/discover 24 ms, first search against the 10,000-belief file 53 ms. Seeding 10,000 beliefs takes 2.2 s on disk.

Gzip sizes and cold-start medians are budgeted in budgets.json and enforced by npm run check.

The model

Concept	Purpose
Belief	A claim held with certainty, evidence, provenance, decay and revision lineage
Dismissal	A record that two semantically close beliefs are intentionally distinct
Flag	A derived attention signal: stale, fading, low-trust, single-evidence or gap
Proximity	Semantic nearness between beliefs, detected on write
Lineage	The revision chain from corrections and supersessions, with version diffs

State is derived, never toggled: freshness, strength, review priority and flags are computed at read time.

Package surface

Import	Contents
@ghostpaw/codex	initCodexTables, read, write, tools, skills, soul, all types
@ghostpaw/codex/mcp	createCodexMcpServer, serveCodexMcp, generic MCP server helpers
ghostpaw-codex (bin)	CLI: tools, describe, call, per-tool flags, mcp, skill
dist/mcp-server.js	Standalone stdio MCP server entry (used by the MCP Bundle and the Dockerfile)
SKILL.md, skills/codex/	Agent Skill with 17 workflow references

ESM and CommonJS, with type declarations for both.

Documentation

Document	Audience
HUMAN.md	Developers using the read / write API
LLM.md	Agent builders wiring soul, tools and skills
docs/README.md	Architecture: model, invariants, scoring, source layout
docs/entities/	Per-entity manuals with exact public API listings
CHANGELOG.md	Release history

Development

npm install
npm run check   # types, lint, zero-deps, tests, build, surfaces, size, API, consumer, startup, ratchet
npm run bench   # hot-path benchmarks at 10,000 beliefs
npm run surfaces  # regenerate SKILL.md, plugin manifests, server.json, mcpb manifest

npm run check is the single gate, locally and in CI. Size budgets (budgets.json) and the public API snapshot (api-surface.json) can only grow with an explicit approval tag in the commit message. The repo is pinned to Node 24.14.0 via .nvmrc.

Support

If this package helps your project, consider sponsoring its maintenance:

Anonyfox • MIT License