Memory OS AI

io.github.romainsantoli-webPublished by GitHub account romainsantoli-webv3.0.1Updated Oct 24, 2026

Adaptive memory for AI agents — FAISS search, chat extraction, cross-project linking

The publisher's own server: Memory.fit

VerifiedSTDIODesktop onlyCloud & InfrastructureFiles & StorageKnowledge & Memory

Overview

AI-generated overview

A local-first semantic memory server that indexes your documents and chat history so any MCP-capable AI assistant can search and recall them across projects.

What you can do
Index folders of PDF, DOCX, TXT, PPTX, image and audio files into a local FAISS vector index, with OCR and Whisper transcription for media and audio files. Run semantic search, keyword occurrence counts, and task-relevant context retrieval over indexed content, and list documents with statistics. Sync and persist conversation messages from Claude, ChatGPT, Copilot and terminal history, auto-detect chat workspaces, and produce a session-start memory briefing. Link or unlink other projects' memories so context is shared across workspaces. Configure cloud storage backends and push, pull or auto-offload memory data when local disk runs low.
When to use it
Useful when you want an assistant to remember documents and past conversations across sessions and projects, especially with a local-first setup where data stays on your machine. Also relevant if you work across several workspaces and want shared recall, or need to search scanned PDFs, images or audio.
Requirements
Local Python 3.10+ process installed from PyPI (memory-os-ai). Optional system tools tesseract for OCR, ffmpeg for audio and antiword for legacy .doc. Optional environment variables MEMORY_CACHE_DIR, MEMORY_MODEL, MEMORY_API_KEY, MEMORY_CLOUD_PROVIDER, MEMORY_CLOUD_CONFIG and MEMORY_DISK_THRESHOLD. Cloud backends need their own credentials and extra packages.
Before you install
The server reads local documents, chat histories and terminal history, so point it only at folders and sources you are comfortable indexing. Cloud overflow can send memory data to third-party providers such as Google Drive, Dropbox, OneDrive, S3, Azure, Box or B2; those need credentials like access tokens, AWS keys or connection strings, which are passed through MEMORY_CLOUD_CONFIG. Tools write, sync and delete index and memory data, including unlinking projects and compacting the index. MEMORY_

Installation

In SourceWeft

  1. Open Memory OS AI in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

Memory OS AI

Adaptive memory system for AI agents — universal MCP server for Claude Code, Codex CLI, VS Code Copilot, ChatGPT, and any MCP-compatible client.

[Tests] [Coverage] [Python] [MCP] [VS Code] [Version] [License]

Concept

Memory OS AI transforms your local documents (PDF, DOCX, images, audio) into a semantic memory queryable by any AI model through the MCP (Model Context Protocol).

┌──────────────────────────────────┐│  AI Client (any MCP-compatible)  ││  Claude Code / Codex / Copilot   ││  ChatGPT / custom agents         │├──────────────────────────────────┤│         MCP Protocol             ││   stdio / SSE / Streamable HTTP  │├──────────────────────────────────┤│      Memory OS AI Server         ││  ┌────────┐  ┌───────────────┐   ││  │ FAISS  │  │ Chat Extractor│   ││  │ Index  │  │ (4 sources)   │   ││  └────────┘  └───────────────┘   ││  ┌────────────────────────────┐  ││  │ Cross-Project Linking      │  ││  └────────────────────────────┘  │└──────────────────────────────────┘

Features

  • 21 MCP tools for memory management, search, chat persistence, project linking, and cloud storage
  • Semantic search with FAISS + SentenceTransformers (all-MiniLM-L6-v2)
  • Multi-format ingestion: PDF, DOCX, TXT, images (OCR), audio (Whisper), PPTX
  • Chat extraction: auto-detects Claude, ChatGPT, Copilot, and terminal history
  • Cross-project linking: share memory across multiple workspaces
  • Cloud storage overflow: auto-backup to Google Drive, iCloud, Dropbox, OneDrive, S3, Azure, Box, B2
  • 3 transports: stdio (default), SSE (--sse), Streamable HTTP (--http)
  • MCP Resources: memory://documents/*, memory://logs/conversation, memory://linked/*
  • Local-first: all data on your machine by default, cloud only when disk runs low

21 MCP Tools

ToolDescription
memory_ingestIndex a folder of documents into FAISS
memory_searchSemantic search across all indexed content
memory_search_occurrencesCount keyword occurrences across documents
memory_get_contextGet relevant context for the current task
memory_list_documentsList all indexed documents with stats
memory_transcribeTranscribe audio files (Whisper)
memory_statusEngine status (index size, model, device)
memory_compactCompact/deduplicate the FAISS index
memory_chat_syncSync messages from configured chat sources
memory_chat_source_addAdd a chat source (Claude, ChatGPT, etc.)
memory_chat_source_removeRemove a chat source
memory_chat_statusStatus of all chat sources
memory_chat_auto_detectAuto-detect chat workspaces on disk
memory_session_briefFull memory briefing for session start
memory_chat_savePersist conversation messages to memory
memory_project_linkLink another project's memory
memory_project_unlinkUnlink a project
memory_project_listList all linked projects
memory_cloud_configureConfigure cloud storage backend for overflow
memory_cloud_statusShow local disk + cloud storage status
memory_cloud_syncPush/pull/auto-sync between local and cloud

Quick Start

Prerequisites

  • Python 3.10+
  • Optional: tesseract (OCR), ffmpeg (audio), antiword (legacy .doc)
bash
# macOSbrew install tesseract ffmpeg antiword
# Ubuntu/Debiansudo apt-get install tesseract-ocr ffmpeg antiword

Install

bash
git clone https://github.com/romainsantoli-web/Memory-os-ai.gitcd Memory-os-aipip install -e ".[dev,audio]"

Auto-Setup (recommended)

bash
# Setup for your AI client:memory-os-ai setup claude-code    # Claude Codememory-os-ai setup codex          # Codex CLImemory-os-ai setup vscode         # VS Code Copilotmemory-os-ai setup claude-desktop # Claude Desktopmemory-os-ai setup chatgpt        # ChatGPT (manual bridge)memory-os-ai setup all            # All of the above
# Check status:memory-os-ai setup status

Manual Start

bash
# stdio (default — Claude Code, VS Code, Codex)memory-os-ai
# SSE transport (port 8765)memory-os-ai --sse
# Streamable HTTP (port 8765)memory-os-ai --http

Project Structure

Memory-os-ai/├── src/memory_os_ai/│   ├── __init__.py          # Public API: MemoryEngine, ChatExtractor, TOOL_MODELS│   ├── __main__.py          # python -m memory_os_ai entry point│   ├── server.py            # MCP server — 21 tools, 3 transports, resources│   ├── engine.py            # FAISS engine — indexing, search, compact, session brief│   ├── cloud_storage.py     # 8 cloud backends (GDrive, iCloud, Dropbox, OneDrive, S3, Azure, Box, B2)│   ├── storage_router.py    # Smart routing: local-first with cloud overflow│   ├── models.py            # 21 Pydantic models + TOOL_MODELS registry│   ├── chat_extractor.py    # 4 extractors: Claude, ChatGPT, Copilot, terminal│   ├── instructions.py      # MEMORY_INSTRUCTIONS for AI clients│   └── setup.py             # Auto-setup CLI for 5 AI clients├── bridges/│   ├── claude-code/         # CLAUDE.md with memory rules│   ├── claude-desktop/      # config.json for Claude Desktop│   ├── codex/               # AGENTS.md for Codex CLI│   ├── vscode/              # mcp.json for VS Code│   └── chatgpt/             # mcp-connection.json for ChatGPT├── tests/                   # 410+ tests — 96% coverage│   ├── test_memory.py       # Engine + models (60 tests)│   ├── test_chat_extractor.py  # Chat extraction (39 tests)│   ├── test_bridges.py      # Bridge configs (22 tests)│   ├── test_gaps.py         # Compact, cross-project, resources (34 tests)│   ├── test_server_dispatch.py # Server dispatch + async (61 tests)│   ├── test_setup.py        # Setup CLI targets│   ├── test_z_coverage_boost.py # Coverage boost (35 tests)│   └── test_zz_full_coverage.py # Full coverage (97 tests)├── pyproject.toml           # v3.1.0 — deps, scripts, coverage config + cloud optional deps├── Dockerfile               # Container deployment└── README.md

Cloud Storage (v3.1.0)

When local disk runs low (< 500 MB free by default), memory data automatically overflows to a configured cloud backend.

Supported Providers

ProviderInstallCredentials
Google Drivepip install memory-os-ai[cloud-gdrive]credentials_json or token_json + folder_id
iCloud Drive(macOS native, no extra deps)container name (default: memory-os-ai)
Dropboxpip install memory-os-ai[cloud-dropbox]access_token + folder
OneDrive(auto-detects mount) or Graph APImount_path or access_token
Amazon S3pip install memory-os-ai[cloud-s3]bucket, aws_access_key_id, aws_secret_access_key
Azure Blobpip install memory-os-ai[cloud-azure]connection_string + container
Boxpip install memory-os-ai[cloud-box]access_token + folder_id
Backblaze B2pip install memory-os-ai[cloud-b2]application_key_id, application_key, bucket_name
All providerspip install memory-os-ai[cloud-all]—

Usage

bash
# Configure via environment (auto-activates on server start)export MEMORY_CLOUD_PROVIDER=icloudexport MEMORY_CLOUD_CONFIG='{"container": "memory-os-ai"}'memory-os-ai
# Or configure at runtime via MCP tool:#   memory_cloud_configure(provider="s3", credentials={"bucket": "my-bucket", ...})#   memory_cloud_status()       → local disk + cloud usage#   memory_cloud_sync("push")   → backup to cloud#   memory_cloud_sync("pull")   → restore from cloud#   memory_cloud_sync("auto")   → offload if disk low

Configuration

Environment Variables

VariableDefaultDescription
MEMORY_CACHE_DIR~/.memory-os-aiCache / FAISS index directory
MEMORY_MODELall-MiniLM-L6-v2SentenceTransformer model name
MEMORY_API_KEY(none)Optional API key for SSE/HTTP auth
MEMORY_CLOUD_PROVIDER(none)Cloud provider name (see table above)
MEMORY_CLOUD_CONFIG(none)JSON credentials or path to JSON file
MEMORY_DISK_THRESHOLD524288000Bytes free before cloud overflow (500 MB)

Development

bash
# Install dev dependenciespip install -e ".[dev]"
# Run testspython -m pytest tests/ -v
# Run with coveragepython -m pytest tests/ --cov=memory_os_ai --cov-report=term-missing
# Coverage threshold: 80% (enforced in pyproject.toml)

License

GNU Lesser General Public License v3.0 (LGPL-3.0). See LICENSE for details.

For commercial licensing, contact [email protected].

Part of the OpenClaw Ecosystem

Memory OS AI is designed to work alongside the OpenClaw agent infrastructure:

RepoDescription
setup-vs-agent-firmFactory for AI agent firms — 28 SKILL.md, 5 SOUL.md, 15 sectors
mcp-openclaw-extensions115 MCP tools — security audit, A2A bridge, fleet management
Memory OS AI (this repo)Semantic memory + chat persistence — universal MCP bridge

Together they form a complete stack: memory (this repo) → skills & souls (setup-vs-agent-firm) → security & orchestration (mcp-openclaw-extensions).

Contributing

Contributions welcome! See CONTRIBUTING.md for guidelines.

⚠️ Contenu généré par IA — validation humaine requise avant utilisation.

Source: README.md at commit b26fbc6

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

1
  1. v3.0.1LatestSep 16, 2026

Score

50% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 days25 pts

    Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.

  • Auth declared10 pts

    Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.

  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts

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