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its-over-9k - The AI Memory Framework

Your AI forgets everything between sessions. its-over-9k fixes that — and a lot more.

It's Over 9000

One load_project() call. ~3000 tokens. Your agent knows everything important about a project — every past mistake, every decision, every open task — across sessions, devices, and AI providers. No setup per conversation. No "let me re-read the codebase." It just remembers.

AI agent? Skip this file. Read AGENT_SETUP.md — written for you, not for humans.


What This Is

its-over-9k is not a note-taking plugin. It's a memory framework for AI agents — a complete infrastructure layer for persistent, portable, token-efficient knowledge that survives session boundaries, device switches, and provider changes.

Four core guarantees:

Pillar

What it means

Token efficiency

5-level lazy loading — you pay for what you read, never more

Portability

Same memory across Claude, Gemini, GPT, local models, any MCP client

Efficient storage

Hierarchical tree structure — context scales with depth, not flat append

No context waste

Auto-session capture + project briefing = zero re-read overhead


Related MCP server: Memsolus MCP Server

The Problem

Every AI session starts from zero. Your agent asks the same questions, makes the same mistakes, contradicts last week's decisions, and wastes 50k tokens loading context it already processed yesterday.

You've tried workarounds — CLAUDE.md files, custom prompts, manually pasting context. They don't scale. You have 10 projects. You switch between 3 devices. You use different AI tools.

The Solution

You:    "Load project"
Agent:  [calls load_project("P0048") — 3000 tokens]
Agent:  "v1.2.9, TypeScript/SQLite/npm. 3 open bugs, 8 roadmap items.
         Last session: rebrand complete, rename_id bug fixed (89 changes).
         Next: O-Entry Auto-Purge. What's the focus today?"

That's it. 3000 tokens for a complete project briefing. The agent knows the stack, the architecture, the open bugs, the recent decisions, and exactly where you left off — even if "you" was a different AI on a different machine yesterday.


How It Works

Level 1  ──  One-line summary          (always loaded — ~5k tokens for 300+ entries)
  Level 2  ──  Paragraph detail        (loaded on demand)
     Level 3  ──  Full context          (loaded on demand)
      Level 4  ──  Extended detail      (loaded on demand)
        Level 5  ──  Raw/verbatim data  (loaded on demand)

At session start, the agent loads Level 1 summaries — one line per memory. When it needs detail, it drills down. Your 300-entry memory costs 5k tokens to overview. A single project costs ~3000 tokens.

Nothing is summarized away. Level 1 is a compressed view, but Levels 2–5 hold the complete original text, word for word, accessible on demand.


Framework Features

Automatic Session Memory

Every conversation is recorded automatically. No "save your work" prompts. No manual checkpoints.

You type  →  Agent responds  →  Stop hook fires  →  Exchange saved to O-entry
                                                   →  Linked to active project
                                                   →  Haiku auto-titles the session

Switch projects mid-session? The O-entry switches too. Start a new session on a different device? The next agent sees every exchange from every device — the conversation never dies.

Haiku Background Checkpoints

Every N exchanges (configurable, default 5), a Haiku subagent wakes up in the background. It reads the recent conversation, extracts lessons learned, errors encountered, and decisions made, then writes them to long-term memory — with full MCP tool access. Your main agent is never interrupted.

The checkpoint also writes a handoff note to the project: "Here's what was done, here's what's in progress, here's the next step." The next agent — on any device, any provider — picks up exactly where you left off.

Project-Based, Not Session-Based

Sessions are meaningless. Projects are everything.

  • O-entries are linked to the active project, not the session

  • Checkpoint counters count project exchanges, not session messages

  • load_project shows recent conversations with full context — across all devices

Skills System

its-over-9k ships with a complete skills layer — structured behavior files that agents load on demand. Skills define how an agent should do something (debug, write memory, curate entries, handle a session start) — separate from memory, separate from prompts.

npx hmem update-skills    # Pull latest skills to your AI tool's skill directory

Skills are versioned and updated independently. Your agents get smarter without reinstalling. 21 skills ship by default:

Skill

Triggers when…

o9k-session-start

Every session start — loads project + surfaces pending git work, open tasks, misrouted O-entries

o9k-using-hmem

Meta-skill loaded at session start; defines mandatory memory habits

o9k-read

Reading from long-term memory (search, prefix filter, find_related, cross-project read)

o9k-write

Writing to hmem — picks prefix, tree location, tags, detects duplicates

o9k-search

User references something without an ID ("the bug we had", "letzte Woche")

o9k-new-project

Creating a P-entry — handles schema, sections, O-entry linking

o9k-new-error

Creating an E-entry with the strict 5-level scaffold

o9k-activate

Switching active project mid-session, plus fixing misrouted exchanges

o9k-context

Loading specific context when load_project output isn't enough

o9k-recall

Dispatching a Haiku sub-agent to search hmem

o9k-dispatch

Dispatching an isolated sub-agent for any search/lookup/calculation

o9k-curate

Cleaning up an .hmem file (mark obsolete, fix titles, consolidate dupes)

o9k-migrate-o

Migrating O-entries to the project-bound 5-level structure

o9k-consolidate

Merging session checkpoint summaries into one final O-entry summary

o9k-wipe

Prep for /clear — save high-value knowledge, update Next Steps

o9k-config

View/change memory settings, hooks, sync, checkpoints

o9k-setup

First-time install of hmem for Claude Code / Gemini CLI / OpenCode

o9k-sync-setup

Set up hmem-sync for cross-device sync

o9k-update

Update flow — runs npm update -g, syncs skills, applies migrations

o9k-release

Pre-publish checklist for its-over-9k itself

o9k-subagent

Template for sub-agents dispatched by o9k-dispatch

Company Memory

Beyond personal memory, agents can maintain a shared company store — a separate company.hmem that multiple agents and team members can read from. Personal and company memory coexist; agents query both simultaneously.

import { openCompanyMemory } from 'its-over-9k';
const store = openCompanyMemory('/path/to/project');

Embeddable SDK

its-over-9k ships as a fully documented TypeScript SDK — import HmemStore directly into your own agents, tools, or automation pipelines:

import {
  HmemStore, openCompanyMemory, resolveHmemPath,
  loadHmemConfig, saveHmemConfig, DEFAULT_CONFIG, DEFAULT_PREFIXES, formatPrefixList,
  searchMemory,
} from 'its-over-9k';
import type {
  AgentRole, MemoryEntry, MemoryNode, HmemConfig,
  SearchResult, SearchOptions, SearchScope,
} from 'its-over-9k';

const store = new HmemStore('/path/to/agent.hmem');
const results = searchMemory('/path/to/project', 'auth token bug', { maxResults: 5 });

MCP Tools

its-over-9k ships two MCP servers:

  • hmem (daily-use, 13 tools) — read, write, search, project lifecycle.

  • hmem-curate (maintenance, 11 tools) — bulk edits, schema migrations, backup/restore. Activate only when curating.

hmem — daily-use server (13)

Tool

What it does

read_memory

5-level lazy read — by ID, prefix, search, time, or tag

write_memory

Create new entries with title, body, tags, links

append_memory

Add child nodes to existing entries

update_memory

Patch fields: title, body, tags, irrelevant, links

search_memory

FTS5 full-text search with sub-node attribution

find_related

Find contextually related entries by tag overlap

load_project

Activate a project + get full briefing + recent sessions

read_project

Read project without activating (comparison/reference)

create_project

Scaffold a new project entry with standard schema

list_projects

List all projects with status summary

flush_context

Persist current session context to long-term memory

move_nodes

Move a subtree under a different parent (also in curate server)

set_active_device

Register and switch between devices

hmem-curate — maintenance server (11)

Tool

What it does

memory_stats

Per-prefix counts, total tokens, favorites, hashtags, stale-list

memory_health

Find broken links, orphan tags, empty entries, dangling chains

export_memory

Export the full .hmem to a portable JSON snapshot

import_memory

Import a JSON snapshot back into a .hmem (destructive)

update_many

Bulk-patch a set of entries (irrelevant, tags, body, etc.)

tag_bulk

Add/remove a tag across many entries

tag_rename

Rename a tag globally across all entries

move_memory

Move an entire entry to a new ID slot

move_nodes

Move a subtree under a different parent (also in main server)

rename_id

Rename an entry's ID; rewrites all inbound links

reset_memory_cache

Invalidate the in-memory L1 cache (after raw SQL writes)

The daily hmem server is registered automatically by hmem init. hmem-curate is opt-in because its tools are destructive — register it when you need to curate:

npx hmem mcp-add-curate          # adds the curate server to Claude Code (user scope)

Then toggle it via /mcp only during curation sessions. For other MCP clients, see Manual setup.


CLI Commands

After npm install -g its-over-9k, the hmem binary is on PATH.

User-facing

Command

Purpose

hmem init

Interactive installer for AI tools (Claude Code, OpenCode, Gemini CLI, Cursor, Windsurf, Cline). Flags: --global / --local / --tools <list> / --dir <path> / --no-example

hmem update-skills

Copy/sync bundled skill files to detected AI tools (called automatically on npm install)

hmem mcp-add-curate

Register the hmem-curate MCP server with Claude Code (opt-in; toggle via /mcp when curating)

hmem doctor

Detect stale or deprecated hmem MCP entries in host configs

hmem stats

Memory statistics + per-project token estimates + 🔴 4k threshold flagging

hmem setup-hook

Re-add the SessionStart hook to Claude Code settings (if removed)

hmem version

Show version

Hook drivers (called by AI tools, not by hand)

Command

Wired into

What it does

hmem hook-startup

UserPromptSubmit

First-message context injection (memory overview, project list, sync status). Periodic checkpoint reminders. Reads JSON from stdin

hmem log-exchange

Stop (sync)

Append the latest exchange to the active O-entry

hmem checkpoint

Stop (async)

Background Haiku/DeepSeek call — extracts lessons, errors, decisions; updates project handoff note

hmem context-inject

SessionStart[clear]

Inject project + rules context after /clear

hmem deactivate

SessionStart[clear]

Clear active project for current session

hmem statusline

statusLine

Render Claude Code statusline (device · active project · checkpoint counter). Reads JSON from stdin

Curation

Command

Purpose

hmem delete <ID>

Permanently delete an entry (curator only, never synced)

hmem migrate-o-entries

Migrate O-entries to the current project-bound schema

hmem summarize-session <id>

Generate a summary node for a session

Sync (requires hmem-sync installed)

Command

Purpose

hmem sync push

Push local memory to the sync server

hmem sync pull

Pull latest memory from the sync server

hmem sync status

Show server URL · auth state · last-sync timestamp

hmem sync setup [--join]

Interactive passphrase + device setup

Backup / migration

Command

Purpose

hmem export-staging <hmem> <json>

Export .hmem SQLite to a portable JSON staging file

hmem import-staging <json> <hmem>

Import a JSON staging file back into a .hmem

hmem serve starts the MCP stdio server directly — your AI tool launches it automatically; you only run it by hand for debugging.


Memory Categories

Default prefixes (configurable via prefixes in hmem.config.json):

Prefix

Category

Example

P

Project

its-over-9k | Active | TS/SQLite/npm

L

Lesson

HMEM_AGENT_ID must be set in hooks — resolveHmemPath falls back to wrong DB

T

Task

T0033 hmem-sync SaaS monetization — recurring monthly tier design

E

Error

158 spurious O-entries created when Haiku MCP lacked HMEM_NO_SESSION guard

D

Decision

Project-based O-entries over session-based — sessions are meaningless

M

Milestone

v1.0.0 — package renamed to its-over-9k, npm rebrand complete

S

Skill

Skill: TypeScript debugging with source maps

N

Navigator

High-level navigation entry (table of contents for a topic)

H

Human

User Skill: TypeScript 9, Architecture 9, React 3

R

Rule

Max one npm publish per day — batch changes

O

Original

Auto-recorded conversation history (every exchange, every device)

I

Infrastructure

Strato Server | Active | Linux | Ubuntu 22.04

C

Convention

Tag scheme: lowercase, prefer existing tags before inventing

Add custom prefixes (e.g. A for App, F for Function reference) by listing them under prefixes in hmem.config.json — they show up in read_memory({ prefix: "X" }) filters automatically.


Quick Start

1. Install

npm install -g its-over-9k

2. Run the interactive installer

npx hmem init

Detects your AI tools, creates the memory directory, configures MCP, and installs all hooks:

Hook

When

What

UserPromptSubmit

Every message

First message: load memory overview. Every Nth: checkpoint reminder

Stop (sync)

Every response

Log exchange to active O-entry

Stop (async)

Every response

Haiku auto-titles untitled sessions

SessionStart[clear]

After /clear

Re-inject project context

3. Verify

Restart your AI tool, then:

read_memory()

Empty response = working (first run). Error = check the troubleshooting section.

Manual setup

{
  "mcpServers": {
    "hmem": {
      "command": "/absolute/path/to/node",
      "args": ["/absolute/path/to/its-over-9k/dist/mcp-server.js"],
      "env": {
        "HMEM_PROJECT_DIR": "/home/yourname/.hmem",
        "HMEM_AGENT_ID": "DEVELOPER"
      }
    }
  }
}

Find the paths:

echo "Node: $(which node)"
echo "Server: $(npm root -g)/its-over-9k/dist/mcp-server.js"
{
  "mcp": {
    "hmem": {
      "type": "local",
      "command": ["/absolute/path/to/node", "/absolute/path/to/its-over-9k/dist/mcp-server.js"],
      "environment": { "HMEM_PROJECT_DIR": "/home/yourname/.hmem" },
      "enabled": true
    }
  }
}

Edit ~/.cursor/mcp.json, ~/.codeium/windsurf/mcp_config.json, or .vscode/mcp.json:

{
  "mcpServers": {
    "hmem": {
      "command": "/absolute/path/to/node",
      "args": ["/absolute/path/to/its-over-9k/dist/mcp-server.js"],
      "env": { "HMEM_PROJECT_DIR": "/home/yourname/.hmem" }
    }
  }
}

Configuration

hmem.config.json in your HMEM_PROJECT_DIR (or Agents/NAME/):

{
  "memory": {
    "maxCharsPerLevel": [200, 2500, 10000, 25000, 50000],
    "maxDepth": 5,
    "checkpointMode": "auto",
    "checkpointInterval": 5,
    "recentOEntries": 10,
    "maxTitleChars": 50,
    "prefixes": { "X": "Custom" }
  },
  "sync": {
    "serverUrl": "https://your-server/hmem-sync",
    "userId": "yourname",
    "salt": "...",
    "token": "..."
  }
}

Key

Default

What it does

checkpointMode

"remind"

"auto" = background agent writes L/D/E. "remind" = prompts the main agent

checkpointInterval

5

Exchanges between checkpoints. 0 = disabled

checkpointProvider

"anthropic"

"anthropic" or "openai" (any OpenAI-compatible: DeepSeek, Groq, …)

checkpointModel

"claude-haiku-4-5-20251001"

Model name for the configured provider

checkpointBaseUrl

OpenAI-compatible base URL (e.g. https://api.deepseek.com/v1)

checkpointApiKeyEnv

provider default

Env var holding the API key. Defaults: ANTHROPIC_API_KEY or OPENAI_API_KEY

recentOEntries

10

How many recent sessions to show in load_project

prefixes

built-in

Add custom entry types

All keys are optional. Missing keys use defaults.

Checkpoint setup per harness

The auto-checkpoint agent runs in the background after every Nth exchange. It needs an LLM call — three paths, picked automatically:

  1. API key in environment (any harness) → direct provider API loop. Configure checkpointProvider + checkpointModel + checkpointApiKeyEnv in hmem.config.json. Works from Pi, Hermes, OpenCode, and Claude Code.

  2. No API key, but claude CLI in PATH → subprocess fallback (claude -p). Zero-config for Claude Code / Claude Max users.

  3. Neither → checkpoint fails with a config-hint error.

Recommended cheap setup (DeepSeek, ~10× cheaper than Haiku):

{
  "memory": {
    "checkpointMode": "auto",
    "checkpointProvider": "openai",
    "checkpointModel": "deepseek-chat",
    "checkpointBaseUrl": "https://api.deepseek.com/v1",
    "checkpointApiKeyEnv": "DEEPSEEK_API_KEY"
  }
}

Then export DEEPSEEK_API_KEY=sk-... in your shell profile. Works for any harness.

Claude Code / Claude Max (zero-config): no provider settings needed — the subprocess fallback uses your existing claude login.

Per-harness exchange logging: Claude Code uses Stop hooks (installed by npx hmem init). Pi uses the built-in extension (src/extensions/pi-hmem.ts). Hermes needs the hermes-hmem plugin (see plugins/hermes-hmem/README.md). OpenCode uses the same hook system as Claude Code.

⚠ Pi users: Hook-based exchange logging is currently not working in the Pi runtime. Exchanges are not saved to O-entries automatically. Manual checkpointing via hmem checkpoint is the workaround until this is resolved.


Cross-Device Sync

Sync memories across all devices with zero-knowledge AES-256-GCM encryption.

npm install -g hmem-sync
npx hmem-sync connect     # Interactive wizard — first device creates, others join

Add HMEM_SYNC_PASSPHRASE to your MCP config for automatic sync on every read/write.

Multi-server redundancy

{
  "sync": [
    { "name": "primary", "serverUrl": "https://server1/hmem-sync", "userId": "me", "salt": "...", "token": "..." },
    { "name": "backup",  "serverUrl": "https://server2/hmem-sync", "userId": "me", "salt": "...", "token": "..." }
  ]
}

Announcements

Broadcast to all synced agents across all devices:

npx hmem-sync announce --message "Server URL changing — update your config!"

Windows

On Windows with Git for Windows, Claude Code routes hook and statusLine commands through Git Bash by default. Git Bash's MSYS2 runtime crashes transiently at startup, killing the command before it runs.

Fix: add "shell": "powershell" to every hook command and to statusLine in ~/.claude/settings.json.

See settings.windows.example.json for the full working config. Key differences:

{
  "env": {
    "HMEM_PATH": "C:/Users/YOUR_USERNAME/.hmem/Agents/DEVELOPER/DEVELOPER.hmem"
  },
  "hooks": {
    "Stop": [{
      "matcher": "",
      "hooks": [{
        "type": "command",
        "command": "node C:/Users/YOUR_USERNAME/AppData/Roaming/npm/node_modules/its-over-9k/dist/cli.js log-exchange",
        "shell": "powershell"
      }]
    }]
  },
  "statusLine": {
    "type": "command",
    "command": "node C:/Users/YOUR_USERNAME/AppData/Roaming/npm/node_modules/its-over-9k/dist/cli.js statusline",
    "shell": "powershell"
  }
}

Run npm root -g to get the correct node_modules path for your machine.

statusLine on Windows: Stable with "shell": "powershell". Without it the statusline disappears intermittently.


Troubleshooting

Problem

Fix

read_memory() fails

Check HMEM_PROJECT_DIR is absolute path and directory exists

nvm: node not found

Use absolute path: which node → use as "command"

Hooks not firing (Claude Code)

Restart Claude Code. Check ~/.claude/settings.json has all 4 hooks

Hooks not firing (Pi)

Known issue — Pi hook integration is currently broken. Use hmem checkpoint manually as a workaround

Exchanges not logged

Check HMEM_AGENT_ID matches your Agents/ directory name

Sync fails

Run npx hmem-sync connect to re-authenticate


Updating

npm update -g its-over-9k    # MCP server + SDK
npm update -g hmem-sync      # Sync (if installed)
npx hmem update-skills       # Refresh skill files

License

MIT

A
license - permissive license
-
quality - not tested
A
maintenance

Maintenance

Maintainers
2dResponse time
0dRelease cycle
15Releases (12mo)
Commit activity
Issues opened vs closed

Resources

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