Skip to main content

◇ OmniMemory

The memory & context layer for coding agents — persistent, branch-aware, git-anchored, fully local. Your AI stops forgetting between chats and stops hallucinating architecture it never verified.

Plugs into Claude Code and Antigravity (more IDEs coming). Toggle with /omni-memory. Browse everything in a minimalist local dashboard.

Install

Option A — Claude Code plugin (no pip needed). The zero-dependency engine rides along inside the plugin, so this is all it takes:

/plugin marketplace add SinghAbhinav04/Omni-Memory
/plugin install omni-memory@singhabhinav

That wires the skill + the capture/inject hooks automatically. Just work — memory injects on every prompt and updates itself when a session ends.

Option B — pip (gives you the omni-memory CLI everywhere).

pip install omni-memory-agent      # or, from a clone: python -m pip install -e .
omni-memory install                # wire it into Claude Code (the CLI is `omni-memory`)
omni-memory build                  # one-time: seed memory from the repo (optional)
omni-memory status

The core is zero-dependency (Python stdlib + SQLite) and runs with no API key. Set GEMINI_API_KEY (or Anthropic/OpenAI) only if you want the AI-written build pass and artifacts.

What it does

  • Remembers decisions, facts, request/data flows, gotchas — automatically at the end of each session, and on demand.
  • Branch-aware — memory is scoped to your git branch; tracks branch creator, timeline, and merge status. Merged branches roll into the base.
  • Enforced — injects a VERIFIED PROJECT MEMORY block into prompts and makes the agent cite what it used, or admit "not in memory" instead of inventing.
  • Relevant (context-aware) — a BM25F ranker (symbol/file/prose field weighting) surfaces the few memories that match your prompt, boosts those anchored to code near what you're editing (via the call graph), and lifts memories the agent has actually cited before. No embeddings, no key.
  • Self-checking (symbol-level)omni-memory check builds a tree-sitter code graph and flags a memory ⚠ stale only when its symbol — or a symbol that calls it — actually changed in git, not just because the file was touched. Falls back to file-level when tree-sitter isn't present.
  • Clean — an extraction-noise filter keeps aspirational prose and doc boilerplate out of the store.
  • Self-cleaning — memories stranded on abandoned branches (deleted unmerged, or long dormant) and long-stale/uncited memories are auto-quarantined (reversible), so false memory doesn't live forever. Memories the agent keeps citing are shielded. gc --dry-run previews; hard-delete stays human-gated.
  • Graph + dashboardomni-memory ui opens a local UI: browsable memory docs, the knowledge graph, and the repo/branch graph.

Commands

omni-memory status | on | off | branch-aware
omni-memory build          # one-time: AI-written facts from the repo + docs
omni-memory ui             # local dashboard (graph + memory docs + repo graph)
omni-memory map            # (re)build the knowledge graph + tree-sitter code graph
omni-memory check          # re-anchor vs git; flag stale memories (symbol-level)
omni-memory recall <q>     # query memory instead of grepping
omni-memory branches       # git topology + per-branch memory
omni-memory remember "…" [--kind decision|fact|flow|gotcha|todo|…]
omni-memory forget <id>
omni-memory used <id> …    # record a citation (feeds the ranker)
omni-memory gc [--dry-run] [--purge]   # quarantine dead/false memory; purge is human-gated
omni-memory restore <id|branch>        # un-quarantine
omni-memory digest         # (re)write the MEMORY.md knowledge base
omni-memory artifact [apimap|linkup|all]   # AI-written cross-reference docs
omni-memory key <gemini|anthropic|openai>  # store a model key securely (chmod 600)
omni-memory install [--platform claude-code|antigravity]

How it works

CAPTURE (session + git) → STORE (SQLite, branch-tagged) → RANK + INJECT + ENFORCE
       → CHECK (staleness vs git) → VISUALIZE (dashboard)

Capture fires from deterministic harness events (UserPromptSubmit → inject, SessionEnd → capture) — never left to the agent's goodwill. Local-first, no cloud, no paid data. See PLAN.md for the full architecture and roadmap.

Status

Core is in: store · git provenance · branch-aware scoping · capture/inject/enforce · context-aware ranker (BM25F + code-graph proximity + citation feedback) · symbol-level staleness · noise filter · memory hygiene (abandoned-branch & false-memory auto-quarantine, human-gated purge) · tree-sitter code graph (Python/JS/TS, with a stdlib-ast fallback) · dashboard (knowledge graph + repo/branch graph). tree-sitter installs automatically on Python ≥3.10; on 3.9 the base install still works and graphs Python via ast. Roadmap: Antigravity via MCP, more languages, runtime request-flow capture. See PLAN.md.

License

MIT © 2026 Abhinav Singh

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

omni_memory_agent-0.9.7.tar.gz (87.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

omni_memory_agent-0.9.7-py3-none-any.whl (83.8 kB view details)

Uploaded Python 3

File details

Details for the file omni_memory_agent-0.9.7.tar.gz.

File metadata

  • Download URL: omni_memory_agent-0.9.7.tar.gz
  • Upload date:
  • Size: 87.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.9.6

File hashes

Hashes for omni_memory_agent-0.9.7.tar.gz
Algorithm Hash digest
SHA256 b1447d3a9610f9fa3f89b295dcb646ed792cc04229d61dacd4a923b31a8e6527
MD5 b6ca03889e74addf67f2b085fcae2f50
BLAKE2b-256 e3366a7d97993e32651cc346cf2c2ca4a94ee64ff2e854001b4c70d157916199

See more details on using hashes here.

File details

Details for the file omni_memory_agent-0.9.7-py3-none-any.whl.

File metadata

File hashes

Hashes for omni_memory_agent-0.9.7-py3-none-any.whl
Algorithm Hash digest
SHA256 cd88bea351c0ef880f10ead87f5640975006b82501f049c2bbad2eab0c186db1
MD5 f06fbf0a99654d0d3b3cc00fcf034e71
BLAKE2b-256 50be3e1153644ae03b588ed03284de08e8a0d7e56ab55bedde953920aeb405bc

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page