GoodMemory

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GoodMemory is a memory layer for AI products and coding agents.

Release source: this is the immutable 0.7.5 stable release source. Registry commands require goodmemory@0.7.5 to be published. The release workflow verifies npm latest and artifact integrity before creating the GitHub Release.

It gives chat apps, copilots, and agent hosts a durable user/project memory loop: write selected facts, retrieve the right context, inject it into the next turn, audit what happened, and delete it when it is wrong.

GoodMemory is not an LLM, agent framework, vector database, or generic RAG system. It is the product memory layer between your app or installed agent host and the model runtime.

What You Get

• Durable memory API: remember, recall, buildContext, feedback, forget, exportMemory, importMemory, and deleteAllMemory.
• Installed agent memory for Codex and Claude Code through goodmemory setup, managed hooks, installed Codex pre-action, goodmemory status, read-only MCP, and opt-in writeback.
• Public write customization with GoodMemoryConfig.remember, RememberProfile, rememberRules, RememberInput.annotations, and named extractor ids.
• Package exports for goodmemory, goodmemory/ai-sdk, goodmemory/host, and goodmemory/http through compiled dist artifacts and TypeScript declarations.
• Local-first storage: Bun gets durable SQLite by default; explicit Postgres, injected adapters, and embedding providers can be added when needed.
• Evaluation and release evidence paths for deterministic tests, live evals, provider-backed evals, package smoke tests, and quality gates.

OpenAI Build Week 2026

Pre-existing foundation. GoodMemory existed before OpenAI Build Week. The pre-event foundation already included the core memory API, local SQLite/Postgres storage, installed-host integration, and the local Inspector. The hackathon entry is the work added after the submission period opened on July 13, 2026, not the entire repository.

Added during Build Week. Dated commits completed and published v0.6.0, strengthened generalized retrieval and iterative-recall verification, added claim-source provenance coverage, hardened installed-host canaries and leakage audits, and expanded the controlled Codex coding-effect evaluation path. Review the pre-event-to-Build-Week diff and its dated commit history for the exact boundary.

How Codex and GPT-5.6 were used. Codex with GPT-5.6 was the primary implementation and verification environment: exploring the repository, implementing and reviewing changes, writing regression tests, reproducing installed-host behavior, and exercising the release and coding-effect evidence paths. GPT-5.6 also powers disclosed non-judge model calls in current evaluation profiles; public-claim paths either use deterministic scoring or keep the judge independent from the answer model.

Run and verify. Install the published 0.7.5 registry baseline and inspect its local memory surface:

npm install -g goodmemory@0.7.5
goodmemory setup --host codex
goodmemory status codex --workspace-root .
goodmemory inspector serve

Verify the repository from source with bun install --frozen-lockfile, bun test, and bun run typecheck. See the Devpost submission and public demo video.

Claim boundary: the submission demonstrates durable cross-session memory, governed writeback, recall evidence, and inspection/deletion infrastructure. It does not claim that GoodMemory has already proven an improvement in Codex coding outcomes; that paired hidden-test evaluation remains an active, fail-closed evidence track.

Start Here: Codex Or Claude Code

npm install -g goodmemory@0.7.5
goodmemory setup

No account or hosted service is required. GoodMemory stores memory locally in SQLite by default, wires lifecycle hooks plus read-only MCP inspection, and keeps durable writeback opt-in. Verify the installation with goodmemory status.

Using another MCP client or integrating an application? Choose an integration path.

Benchmark Results

GoodMemory separates current-production claims, versioned historical evidence, and internal research. A number may enter the current-claims table only after gate:public-benchmark-claim --strict validates a committed declaration for the current package version: complete coverage, executionFailures: 0, a no-memory baseline, deterministic scoring or an independent judge, verified dataset source and license, and a reproducible run (commit + command + package version). No end-to-end benchmark runner is allowlisted today, so promotion is unavailable for both current and historical rows. Stored-answer rescores and legacy presentation projections cannot open that boundary or supply README score and disclosure fragments as self-attestation.

GoodMemory 0.7.5 has no current or versioned historical benchmark claim. The retained v0.7.3 LoCoMo projection is not end-to-end runner evidence, so it is an internal diagnostic. The v0.6.0 LoCoMo, BEAM, and MemoryAgentBench measurements and ImplicitMemBench are also internal diagnostics under the same fail-closed boundary. LongMemEval is withdrawn pending a clean rerun: the historical rules-only path used answer annotations, and the later label-free path exposed raw answer_* session IDs to retrieval and the reader. ImplicitMemBench's retry-merged result remains internal evidence because it does not replace a monolithic fresh run. HaluMem, MemGym, and MINTEval remain release evidence rather than public benchmark claims.

No benchmark result is currently presented as measured on 0.7.5.

Versioned evidence

No end-to-end benchmark runner is currently allowlisted for versioned evidence.

No benchmark result currently qualifies as versioned historical evidence.

The retained v0.7.3 LoCoMo projection remains available in the repository for audit, but it is not shipped as a verified package artifact and cannot authorize a public or versioned claim. Old artifacts will not be retrofitted; a future producer and its verifier must be implemented together before promotion opens.

Where both are available, a row reports two tracks. The strict track is deterministic or judge-free — a hard lower bound no LLM judge can inflate. The second track re-judges the same stored answers (not regenerated) under a benchmark-source or industry-standard prompt. Numerical comparability is claimed only when the pinned evaluator model and remaining benchmark configuration also match. Every per-protocol detail is recorded in the linked declarations.

The LongMemEval declaration is now paused_boundary, not historical evidence. Its old numeric artifacts remain only to preserve the audit trail. They must not be quoted as GoodMemory results until an opaque-session-id, label-free full rerun replaces them; see the withdrawal declaration. The v0.6.0 BEAM, MemoryAgentBench, and LoCoMo measurements remain internal diagnostics. They do not pass the empty end-to-end runner allowlist, so they are not versioned historical evidence.

The ImplicitMemBench Full-300 stored-answer rescore uses the canonical zero-failure run-phase61-full300-rerun-20260706-codex-current answers, then re-scores the same stored answers with gpt-5.4 (sourceAnswersUnchanged: true). The judge is cross-version but the same GPT family as the gpt-5.5 answer model, not a cross-family judge. The recorded score is 0.691 (207.35/300) versus an upstream-chat baseline of 0.400 (120/300), with 530 judge-required row decisions across the baseline and GoodMemory arms; deterministic structured_first_action rows are carried forward rather than judged. The older same-model diagnostic score was 0.708 and is not the recorded result. The freshest clean answer-regeneration drift check after recent code changes scored 0.6895 with executionFailures: 0; it shows current checkout drift, not a replacement for the stored-answer comparability artifact. Its measured sources do not independently expose both package version and commit at explicit JSON paths, so the result is paused as an internal diagnostic and is not versioned historical evidence. Dataset CC BY 4.0, fetched at eval time, never vendored.

Internal diagnostics (not public claims)

LongMemEval's first current-recall assembly development slice is superseded: although its reader context hid raw session IDs, the memory-builder boundary still received gold-bearing session IDs and turn markers. A stricter v2 protocol now removes answers, question type, answer markers, and raw session identities before memory construction. Its development slice must be rerun on a clean commit before the still-sealed holdout can be opened; no LongMemEval claim is restored. ImplicitMemBench's explicit retry-merged check reaches 0.6923666667 with zero failures, but it is not a replacement monolithic fresh Full-300 run. Both therefore remain outside the current-claims table. The underlying reports live under gitignored reports/ and are reproducible from the recorded commands.

Use task-board/00-README.txt for execution order and docs/GoodMemory-Current-Status-and-Evidence.md for claim boundaries.

Choose Your Integration Path

GoodMemory has three primary product entry points. They are not the only APIs: lower-level surfaces such as goodmemory/host, custom stores, eval tooling, and runtime helpers support these paths. They are the README-level ways to decide how to start.

Autonomous agent? Start here

If you are an agent that wants to give yourself durable memory, match one path and run it. Machine-readable versions of this tree live in llms.txt and .well-known/goodmemory.json (a deployed bridge also serves the descriptor at /.well-known/goodmemory.json).

• You are, or run inside, Claude Code or Codex → npm install -g goodmemory@0.7.5 && goodmemory setup. Unsure what is already wired? Run goodmemory adopt (add --json for a machine-readable plan): it inspects .claude/, .codex/, and existing MCP config, then prints the exact next command for your environment.
• You speak MCP (Cursor, Windsurf, Cline, Claude Desktop, Gemini CLI, OpenCode, or a custom client) → add the standalone MCP server; the two tools you need are goodmemory_get_context (recall) and goodmemory_remember (opt-in write).
• You are a framework agent or a backend → call the HTTP bridge: hosted at goodmemory.vibenest.net or self-hosted with goodmemory-http-bridge --recommended (or GOODMEMORY_PROFILE=agent-recommended goodmemory-http-bridge); Python callers use pip install goodmemory-client.

The prose paths below expand each option.

1. Build Memory Into An Agent, Chatbox, Or Copilot

Use this when you own the product server and the model call. Install goodmemory in your Node/Bun service, create one memory instance, and pass a stable scope such as userId, workspaceId, sessionId, and optionally agentId.

The request flow is:

1. Before the model call, run recall() for the current scope and query.
2. Run buildContext() to turn recall hits into a prompt fragment.
3. Call your model with that memory context.
4. After the response, write selected signals with memory.jobs.enqueueRemember() or remember().
5. Use feedback(), targeted reviseMemory(), forget(), and exportMemory() for correction, deletion, and user audit; importMemory() restores an export or ingests a directory of Markdown pages as note memories.

If your server already uses Vercel AI SDK, use goodmemory/ai-sdk to wrap generateText() or streamText() instead of hand-wiring the whole loop. Start with App Quickstart, then read AI SDK Adapter if you use AI SDK.

2. Add Memory To Codex Or Claude Code

Use this when you want an installed coding agent to remember project and user context without changing the agent itself. Install the global CLI and run goodmemory setup.

The installed-host flow is:

1. session-start injects a session brief; user-prompt-submit injects per-prompt context (relevance-gated on fresh installs so low-signal prompts stay clean).
2. The Claude Code Stop hook captures each turn from the session transcript (transcript_path) into governed writeback candidates — bounded, redacted, never raw transcripts; for Codex, goodmemory codex writeback --from-rollout feeds the newest session rollout through the same pipeline.
3. Codex pre-tool-use can deny or redirect risky Bash through goodmemory codex action on the same installed config and storage path.
4. MCP gives trace, context, stats, and artifact inspection; the goodmemory_remember write tool is opt-in via mcp.allowWrite (or goodmemory enable <host> --mcp-allow-write).
5. Writeback stays off for scripted installs; interactive install and goodmemory setup --recommended (one consent prompt) enable selective durable writes — auditable via writeback inspect, reversible via writeback forget --event-id.
6. Fresh installs start on the measured BM25 hybrid retrieval tier with a 1024-token session brief and 512-token gated prompt injection; goodmemory status shows the retrieval tier, capture proof-of-life, and injection telemetry. Optional sharedAgents config lets one host read the other host's records (writes stay attributed).

Start with Quickstart: Codex Or Claude Code Memory. Use Installed Host Writeback when you are ready to review or enable writes.

3. Deploy GoodMemory As A Backend Memory-Layer Service

Use this when another backend should call GoodMemory as a service, especially when the product backend is Python/FastAPI or when a product such as OneLife should keep memory server-side instead of bundling GoodMemory into a mobile or browser client.

Deploy the packaged goodmemory-http-bridge in a Node/Bun sidecar. Your backend then calls:

• /memory/recall-context before its own model call
• /memory/remember after a user-confirmed or product-approved signal
• /memory/feedback for procedural corrections
• /memory/export and /memory/forget for audit and deletion
• /memory/revise for targeted correction by explicit memory id
• /memory/import for restoring an export or ingesting Markdown pages

Your service still owns auth, product policy, UI, and model orchestration. GoodMemory owns memory storage, recall, context assembly, write governance, and audit/export/delete behavior. Start with Python/FastAPI HTTP Bridge — the official Python client (pip install goodmemory-client) and a hosted bridge instance at goodmemory.vibenest.net are documented there — then check Runtime And Storage for SQLite/Postgres choices.

During a model turn, GoodMemory does four jobs:

1. Resolve memory for the current scope.
2. Build a prompt-ready context fragment.
3. Record selected post-response signals when your app or host allows it.
4. Provide audit, correction, export, and deletion paths for user control.

Your app or installed agent still owns auth, UI, model calls, and product policy. GoodMemory owns the memory loop and storage boundary.

Install

The published registry baseline is GoodMemory 0.7.5. Use the pinned registry commands below for reproducible installs.

Use the global CLI when you want memory enhancement inside installed coding agents:

npm install -g goodmemory@0.7.5
goodmemory setup
goodmemory status

Use the package dependency when you are building an application:

npm install goodmemory@0.7.5

If you want to type goodmemory directly, install the global CLI. A project-local npm install goodmemory@0.7.5 does not put goodmemory on your shell PATH. Use npx goodmemory, npm exec -- goodmemory, or ./node_modules/.bin/goodmemory from that project instead.

npx goodmemory -V

Bun consumers can install it directly:

bun add goodmemory@0.7.5

Tarball verification for this release source:

npm install ./goodmemory-0.7.5.tgz

The installed CLI is Bun-backed for non-version commands. The package bin is Node-safe for goodmemory -V and goodmemory --version; other commands delegate to Bun.

Quickstart: Codex Or Claude Code Memory

For most users, the first useful path is installed-host memory.

npm install -g goodmemory@0.7.5
goodmemory setup
goodmemory status

goodmemory setup detects Codex and Claude Code, installs managed host wiring, and asks for:

• host: codex, claude, or both detected hosts
• activation: global, current workspace, or manual opt-in
• GoodMemory user id
• optional Postgres storage
• optional embedding provider
• optional LLM extraction provider
• writeback mode: off, observe, review, or selective

Interactive setup defaults to global activation with workspace-derived isolation and recommends selective for new host configs so high-signal writes start working immediately with audit and undo. Choose review when you want Inspector approval before durable writes. Existing host configs keep their current writeback mode when the interactive prompt default is accepted. Scripted installs stay safe with --json or --no-interactive. Skipping provider setup is valid: GoodMemory still works with local SQLite and rules-only extraction.

Useful commands:

goodmemory setup --host codex
goodmemory status codex --workspace-root .
goodmemory enable codex --workspace-root . --writeback observe
goodmemory enable codex --workspace-root . --writeback selective
goodmemory disable codex --workspace-root .
goodmemory uninstall codex

The installed host path has four pieces:

• Managed pre-action for Codex: pre-tool-use can deny or redirect risky Bash and goodmemory codex action executes the vetted first step on the same installed config, storage, provider, and scope path used by recall and writeback.
• Recall injection: session-start and user-prompt-submit hooks call recall() plus buildContext() and fail open if config, parsing, or storage is unavailable.
• Deep inspection: goodmemory mcp serve --host codex and goodmemory-mcp --host codex expose read-only context, trace, stats, and artifact tools.
• Optional writeback: session-stop and explicit writeback commands can turn selected after-response signals into durable memory.

Standalone MCP For Any Client

Hosts without a managed install path (Cursor, Windsurf, Cline, Claude Desktop, Gemini CLI, OpenCode, or your own MCP client) can run the same MCP server in standalone mode — no goodmemory setup, no host config files. Scope and storage come from flags/env; the served surface is the same 8 read-only tools, plus an opt-in governed write tool:

{
  "mcpServers": {
    "goodmemory": {
      "command": "goodmemory-mcp",
      "args": ["--standalone", "--user-id", "YOUR_USER_ID"]
    }
  }
}

Equivalent invocation: goodmemory-mcp --standalone --user-id <id> (requires Bun on PATH; GOODMEMORY_USER_ID works as the flag's env fallback). --allow-write (or GOODMEMORY_MCP_ALLOW_WRITE=1) registers goodmemory_remember, which writes through the normal governed remember pipeline, and goodmemory_write_note, which stores an authored page (prose or Markdown, up to 8 KB) verbatim as a note and supersedes it by title on rewrite. Agent-tagged memories written by installed hosts stay private to their agent; add --agent-id codex plus the shared --storage-url to opt into reading an installed host's store. Full flag/env matrix, scope notes, and per-host recipes: docs/GoodMemory-Standalone-MCP-Setup-Guide.md (Cursor · Gemini CLI · OpenCode).

Installed Host Writeback

Installed Host Writeback is opt-in. Runtime config defaults and new scripted installs remain off unless the user explicitly chooses a writeback mode. Existing configs keep their current writeback mode when no explicit override is provided. New interactive installs recommend selective so high-signal writes start working immediately with audit and undo; choose review when you want Inspector approval before durable writes.

Use observe before selective:

goodmemory enable codex --writeback observe
goodmemory codex writeback --json

goodmemory enable codex --writeback review
goodmemory inspector serve

goodmemory enable codex --writeback selective
goodmemory codex writeback --json

goodmemory inspector serve opens the built-in local React console for users and scopes, categorized memory and supersession history, candidate decisions, recall evidence traces, and audit events. The startup token is passed in a URL fragment, cleared immediately into session storage, and sent only as a Bearer header. Revision and destructive actions require confirmation, ETags, and idempotency keys. See Inspector And Admin API.

Writeback rules:

• off: no after-response memory extraction.
• observe: store local bounded/redacted candidate previews for review without raw transcripts or durable memory writes.
• review: queue bounded/redacted candidates for Inspector approval; no durable memory is written until an operator approves a candidate.
• selective: write selected candidates through the public remember surface.
• Raw transcripts are not persisted as memory.
• Assistant-originated durable memory is blocked unless the host confirms or verifies it and the active profile allows it.
• remember: "never" masks annotated content before deterministic, custom, or assisted extraction.

Audit and undo:

goodmemory codex writeback inspect --json
goodmemory codex writeback forget --event-id <event-id> --review-outcome false_write

The audit ledger stores bounded redacted candidate previews, candidate keys, typed linked record ids, status, reasons, host, mode, timestamps, scope/session digests, and optional manual review metadata. It does not store raw host payloads. forget --event-id deletes linked memory/evidence records through public forget() before marking durable audit events forgotten; for observe-only events it marks the candidate dismissed without calling forget().

Claude Code has deterministic CLI parity for hook and writeback commands; Codex is the canonical live-evidence path.

Scripted Host Install

Use goodmemory install <host> when you want a fully non-interactive setup:

goodmemory install codex \
  --user-id <user-id> \
  --activation-mode global \
  --writeback observe \
  --storage-provider postgres \
  --storage-url "postgres://user:pass@host:5432/goodmemory" \
  --embedding-provider openai \
  --embedding-model text-embedding-3-small \
  --embedding-api-key <key> \
  --llm-provider openai \
  --llm-model gpt-4o-mini \
  --llm-api-key <key> \
  --no-interactive