Skip to main content

🧠 agy-mem

Autonomous Background Memory, Observation Extractor & Fast Recall Engine for Google Antigravity (agy)

Persistent cross-session intelligence and sub-millisecond retrieval with zero external dependencies.

License: MIT Python 3.8+ Zero Dependencies Model Context Protocol


⚡ The Problem & The Solution

When working with AI coding agents like Google Antigravity (agy), starting a new session often means starting with amnesia. You find yourself repeatedly explaining project architectures, database schemas, prior bugfixes, and coding preferences.

Tools like claude-mem and antigravity-memory attempt to solve this, but require heavy Node.js runtimes, hundreds of megabytes of node_modules, and external API keys to pay for AI summarizations.

agy-mem solves this natively:

  1. 0 Dependencies: Pure Python 3 standard library with native SQLite FTS5 and BM25 ranking.
  2. Native Trajectory Observer: Reads directly from Antigravity's internal brain/*/transcript.jsonl and conversation databases. It extracts tools called, exact files modified, and assistant outcomes without burning API tokens.
  3. Official MCP Server: Speaks standard Model Context Protocol (JSON-RPC 2.0 stdio), exposing search, recall, get_observations, timeline, and sync.
  4. Sub-50ms Latency: Instant terminal search and prompt recall.

📊 Comparison

Feature antigravity-memory (npm) claude-mem agy-mem (This Project)
Language Node.js / TypeScript Node.js / Webpack Pure Python 3
External Dependencies Heavy (npm, better-sqlite3) Heavy (npm, ChromaDB) 0 (Python Standard Library)
Install Footprint ~100 MB+ ~120 MB+ ~35 KB (Single file)
Data Ingestion Manual tool calls Claude hook / daemon Automatic Trajectory Observer
API Cost / Quota Calls Gemini API for summaries Calls Claude API $0 / Zero token cost
Search Engine Basic SQL Vector embeddings SQLite FTS5 with BM25
MCP Compliance Yes Yes Yes (JSON-RPC 2.0 stdio)
Historical Backfill Future sessions only Future sessions only Instant full-history backfill

🚀 Quick Install (1-Liner)

Install agy-mem, register the MCP server, and add the /recall & /mem slash commands in a single command:

curl -sSL https://raw.githubusercontent.com/Cancelllls/agy-mem/main/install.sh | bash

Or Clone & Install Manually

git clone https://github.com/Cancelllls/agy-mem.git
cd agy-mem
chmod +x install.sh
./install.sh

💡 How to Use

1. In Any Terminal

# Search memories with high-visibility formatted cards
agy-mem search "fiqh zakat"
agy-mem search "statusline timeout" -p Antigravity

# Recall context formatted for prompt injection
agy-mem recall "offline barcode scanner"

# View chronological timeline (latest first, or origin first)
agy-mem timeline --limit 5
agy-mem timeline --earliest --limit 3

# Check database health & breakdown by project
agy-mem status

# Manually store a technical observation
agy-mem add --project Aya --type architecture --title "WAL Mode SQLite" --narrative "Enabled WAL mode and memory pragmas."

# Trigger incremental sync of newly completed turns
agy-mem sync

2. Inside Google Antigravity (agy prompt)

agy-mem installs native slash commands in ~/.agent/skills/:

  • /recall <topic>: Injects past decisions, bugfixes, and code files directly into your active prompt context.
  • /mem: Displays the live memory dashboard, synced session counts, and database health.

3. As an MCP Server (Model Context Protocol)

agy-mem automatically registers itself in ~/.gemini/config/mcp_config.json:

{
  "mcpServers": {
    "agy-mem": {
      "command": "/home/ubuntu/.local/bin/agy-mem",
      "args": ["mcp"]
    }
  }
}

Any MCP-compatible AI agent can now call:

  • search: Full-text memory search with BM25 scoring.
  • get_observations: Fetch complete details and diffs for observation IDs.
  • recall: Markdown context block formatted for immediate reasoning.
  • timeline: Chronological event sequence.
  • add_observation: Store new decisions programmatically.
  • sync: Trigger background observation extraction.

🏗️ Architecture

flowchart TD
    subgraph Antigravity ["Google Antigravity Runtime"]
        B["brain/*/transcript.jsonl"]
        C["conversations/*.db"]
    end

    subgraph agyMem ["agy-mem Engine"]
        Obs["Trajectory Observer & Turn Parser"]
        FTS["SQLite FTS5 Engine\n(~/.gemini/antigravity-cli/memory.db)"]
        BM["BM25 Ranking & Indexer"]
    end

    subgraph Interfaces ["Access Interfaces"]
        CLI["CLI: agy-mem search / timeline"]
        Slash["Slash Commands: /recall, /mem"]
        MCP["MCP Server: stdio JSON-RPC"]
    end

    B --> Obs
    C --> Obs
    Obs --> FTS
    FTS --> BM
    BM --> CLI
    BM --> Slash
    BM --> MCP

📄 License

MIT License © 2026 Abdalrahman Samir / Cancellls. See LICENSE for details.

Metadata

Release files for agy-mem 1.0.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for agy-mem 1.0.0
File Size Uploaded
agy_mem-1.0.0.tar.gz 14.5 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for agy-mem 1.0.0
File Interpreter ABI Platform
agy_mem-1.0.0-py3-none-any.whl Python 3 none any Details

Total release size: 29.2 kB

Release files / agy_mem-1.0.0.tar.gz

Download URL agy_mem-1.0.0.tar.gz
Size 14.5 kB
Tags Source
SHA-256 checksum
How to use checksums
ff85964403ed3ae26dfb7533c2711d3583b60209273d057ef8710c0f040c6878
BLAKE2b-256 checksum
How to use checksums
17155076367f8e72a35066e8e421146601d60e6d770fc5201b08b52e652e7472
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.3

Release files / agy_mem-1.0.0-py3-none-any.whl

Download URL agy_mem-1.0.0-py3-none-any.whl
Size 14.7 kB
Tags Python 3
SHA-256 checksum
How to use checksums
a1628d6a094ca848532565764de8326d6ca275cd83f12f87e4bd4c8cc3cd4b12
BLAKE2b-256 checksum
How to use checksums
d0b2d127cee8ab3781ae872f8d953f6d837fd13fea98d766e31b92449a5cda3f
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.3

Release history Release notifications | RSS feed

1.0.3

2 release files

1.0.2

2 release files

1.0.1

2 release files

This release

1.0.0 This release

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page