MemoV
Provides a memory layer for AI coding agents with Git-powered version control, enabling automatic tracking of prompts, context, and code diffs.
README
<p align="center"> <a href="https://github.com/memovai/memov"> <img src="docs/images/memov-banner.png" width="800px" alt="MemoV - The Memory Layer for AI Coding Agents"> </a> </p>
<p align="center"> <b>English</b> | <a href="docs/readme/README_DE.md">Deutsch</a> | <a href="docs/readme/README_ES.md">Español</a> | <a href="docs/readme/README_FR.md">Français</a> | <a href="docs/readme/README_JA.md">日本語</a> | <a href="docs/readme/README_KO.md">한국어</a> | <a href="docs/readme/README_PT.md">Português</a> | <a href="docs/readme/README_RU.md">Русский</a> | <a href="docs/readme/README_CN.md">中文</a> </p>
<h4 align="center">VibeGit🤌: Auto-trace your prompts, context & code diffs.</h4>
<div align="center">
</div>
MemoV is a memory layer for AI coding agents that provides traceable, Git-powered version control for prompts, context, and code diffs. It enables VibeGit - automatic versioning of AI coding sessions with branch exploration, rollback capabilities, and zero pollution to the standard .git repository.
<div align="center">
| MemoV | Checkpoints |
|---|---|
| Branch exploration | Linear timeline |
| Cross-session | Session-bound |
| Rollback preserves all | Rollback erases history |
| Every jump tracked | No trajectory |
</div>
<!-- <p align="center"> <img src="docs/images/readme.gif" alt="MemoV Demo" width="800px"> </p> -->

- 💬 Join our Discord and dive into smarter vibe engineering
<!-- <div align="center">
</div> -->
Features
- One-click MCP: Works with any AI coding agent
- VibeGit for Agents: Auto-trace prompts, context, and code diffs before git commits
- Version Control: Branch, rollback, replay any interaction
- Keep Git Clean: Shadow
.memtimeline, files as context, zero pollution on.git - Visual UI: Say "mem ui" in chat, and view at http://localhost:38888
- Private-first — Local, no database, no overhead. Use .memignore to exclude

Quick Start (MCP Installation)
Prerequisites
Install uv first:
# macOS / Linux
curl -LsSf https://astral.sh/uv/install.sh | sh
# Windows
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
# Install Git (if not installed)
winget install --id Git.Git -e --source winget
Claude Code
Run in your project root directory:
claude mcp add mem-mcp --scope project -- uvx --from git+https://github.com/memovai/memov.git mem-mcp-launcher stdio $(pwd)
Codex
Run in your project root directory:
codex mcp add mem-mcp -- uvx --from git+https://github.com/memovai/memov.git mem-mcp-launcher stdio $(pwd)
<details> <summary><b>VS Code</b></summary>
Create .vscode/mcp.json in your project root:
{
"servers": {
"mem-mcp": {
"type": "stdio",
"command": "uvx",
"args": [
"--from",
"git+https://github.com/memovai/memov.git",
"mem-mcp-launcher",
"stdio",
"${workspaceFolder}"
]
}
}
}
</details>
<details> <summary><b>Cursor</b></summary>
Go to Files > Preferences > Cursor Settings > MCP, then add:
{
"mcpServers": {
"mem-mcp": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/memovai/memov.git",
"mem-mcp-launcher",
"stdio",
"${workspaceFolder}"
]
}
}
}
</details>
<details> <summary><b>Antigravity</b></summary>
Note: Antigravity does not support
"${workspaceFolder}"variable. Please manually enter the absolute path to your project directory.
Go to Settings > MCP, then add:
{
"mcpServers": {
"mem-mcp": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/memovai/memov.git",
"mem-mcp-launcher",
"stdio",
"/absolute/path/to/your/project"
]
}
}
}
Replace /absolute/path/to/your/project with the actual absolute path to your project directory (e.g., /Users/username/projects/my-project on macOS/Linux or C:\\Users\\username\\projects\\my-project on Windows).
</details>
<details> <summary><b>With VectorDB (RAG mode)</b> 🚧 WIP</summary>
To enable semantic search, validation, and debugging tools, install with [rag] extras:
Claude Code:
claude mcp add mem-mcp --scope project -- uvx --from "git+https://github.com/memovai/memov.git[rag]" mem-mcp-launcher stdio $(pwd)
VS Code / Cursor: Change the --from argument to:
"git+https://github.com/memovai/memov.git[rag]"
</details>
Important Tips
Add a Rule — To automatically save snapshots after each interaction, add a rule to your coding agents:
- Cursor: Cursor Settings > Rules
- Claude Code:
CLAUDE.md - Or the equivalent in your MCP client
Example rule:
After completing any interaction, always call `use mem snap` to save the snapshot.
Web UI, Just Say Use mem ui🤌
Just say "use mem ui" in the chat — opens at http://localhost:38888 with timeline view, branch filtering, diff viewer, and jump to any snapshot.
CLI Installation (Optional)
If you want to use the mem CLI tool directly (for manual tracking, history viewing, etc.):
One-Line Install
curl -fsSL https://raw.githubusercontent.com/memovai/memov/main/install.sh | bash
Or with wget:
wget -qO- https://raw.githubusercontent.com/memovai/memov/main/install.sh | bash
Package Managers
<details> <summary><b>Homebrew (macOS/Linux)</b></summary>
brew tap memovai/mem
brew install memov
</details>
<details> <summary><b>APT (Debian/Ubuntu)</b></summary>
echo "deb [trusted=yes] https://memovai.github.io/memov/apt stable main" | sudo tee /etc/apt/sources.list.d/mem.list
sudo apt update
sudo apt install mem
</details>
<details> <summary><b>YUM/DNF (Fedora/RHEL/CentOS)</b></summary>
sudo curl -o /etc/yum.repos.d/mem.repo https://memovai.github.io/memov/yum/mem.repo
sudo dnf install mem
</details>
<details> <summary><b>Direct Download</b></summary>
Download the latest release for your platform:
| Platform | Download |
|---|---|
| Linux x86_64 | mem-linux-x86_64.tar.gz |
| macOS Intel | mem-macos-x86_64.tar.gz |
| macOS Apple Silicon | mem-macos-arm64.tar.gz |
| Windows x86_64 | mem-windows-x86_64.exe.zip |
Linux / macOS:
curl -LO https://github.com/memovai/memov/releases/latest/download/mem-linux-x86_64.tar.gz
tar -xzf mem-linux-x86_64.tar.gz
sudo mv mem-linux-x86_64 /usr/local/bin/mem
mem --help
Windows (PowerShell):
Invoke-WebRequest -Uri "https://github.com/memovai/memov/releases/latest/download/mem-windows-x86_64.exe.zip" -OutFile "mem.zip"
Expand-Archive -Path "mem.zip" -DestinationPath "."
New-Item -ItemType Directory -Force -Path "$env:ProgramFiles\mem"
Move-Item -Path "mem-windows-x86_64.exe" -Destination "$env:ProgramFiles\mem\mem.exe"
[Environment]::SetEnvironmentVariable("Path", $env:Path + ";$env:ProgramFiles\mem", "Machine")
mem --help
</details>
<details> <summary><b>From Source</b></summary>
Requires Python 3.10+ and uv:
git clone https://github.com/memovai/memov.git
cd memov
uv sync
uv pip install -e .
mem --help
</details>
Installation for Contributors
Please see docs/installation_for_dev.md for detailed installation instructions.
Architecture
MemoV follows a three-tier architecture with MemovManager as the central orchestrator, the MCP Server as an adapter layer for AI agents, and an optional RAG system for semantic search.

<details> <summary><b>MCP Tools</b></summary>
Core Operations
-
snap(user_prompt: str, original_response: str, agent_plan: list[str], files_changed: str)- Record every user interaction with automatic file tracking. Handles untracked vs modified files intelligently.
-
mem_ui(port: int = 38888)- Launch the Web UI at
http://localhost:38888to visually browse history, view diffs, and jump to any snapshot.
- Launch the Web UI at
-
mem_history(limit: int = 20, commit_hash: str = "")- View memov history with prompts, responses, and file changes.
-
mem_jump(commit_hash: str)- Jump to a specific snapshot, restoring all tracked files and creating a new branch.
RAG Tools (requires [rag] extras)
These tools are only available when installed with [rag] extras.
-
mem_sync()- Sync all pending operations to VectorDB for semantic search capabilities.
-
validate_commit(commit_hash: str, detailed: bool = True)- Validate a specific commit by comparing prompt/response with actual code changes. Detects context drift and alignment issues.
-
validate_recent(n: int = 5)- Validate the N most recent commits for alignment patterns. Useful for session reviews and quality assurance.
-
vibe_debug(query: str, error_message: str = "", stack_trace: str = "", user_logs: str = "", models: str = "", n_results: int = 5)- Debug issues using RAG search + multi-model LLM comparison. Searches code history for relevant context and queries multiple AI models (GPT-4, Claude, Gemini) in parallel for diverse debugging insights.
-
vibe_search(query: str, n_results: int = 5, content_type: str = "")- Fast semantic search through code history (prompts, responses, agent plans, code changes) without LLM analysis. Perfect for quick context lookup.
Health Check
GET /health- Returns "OK". Useful for IDE/agent readiness checks.
</details>
License
MIT License. See LICENSE.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.