# MCP Memory Server
A persistent vector memory server for Windsurf, VS Code, and other MCP-compliant editors.
## Features
- **Local Vectors**: Uses `LanceDB` and `all-MiniLM-L6-v2` locally. No API keys required.
- **Persistence**: Memories are saved to disk (`./mcp_memory_data`).
- **Isolation**: Supports multiple projects via `project_id`.
## Installation
You need Python 3.10+ installed.
1. **Setup Virtual Environment**
It's recommended to use a virtual environment to avoid conflicts.
```bash
python3 -m venv .venv
source .venv/bin/activate
```
2. **Install Dependencies**
```bash
pip install -e .
```
## Configuration
Add this to your `mcpServers` configuration (e.g., in `~/.codeium/windsurf/mcp_config.json` or VS Code MCP settings).
### Windsurf / VS Code Config
Replace `/ABSOLUTE/PATH/TO/...` with the actual path to this directory.
```json
{
"mcpServers": {
"memory": {
"command": "/ABSOLUTE/PATH/TO/mcp-memory-server/.venv/bin/python",
"args": [
"-m",
"mcp_memory.server"
],
"env": {
"MCP_MEMORY_PATH": "/ABSOLUTE/PATH/TO/mcp-memory-server/mcp_memory_data"
}
}
}
}
```
## Usage
### Ingestion
Use the included helper script `ingest.sh` to ingest context files.
```bash
# General Usage
./ingest.sh --project <PROJECT_NAME> <FILES...>
```
**Real Example (Project "Thaama"):**
```bash
/ABSOLUTE/PATH/TO/mcp-memory-server/ingest.sh --project project-thaama \
/path/to/PROJECT_CONTEXT.md \
/path/to/DECISIONS.md \
/path/to/AI_RULES.md
```
### Tools
The server exposes:
- `memory_search(project_id, q)`
- `memory_add(project_id, id, text)`
## Troubleshooting
- **First Run**: The first time you run it, it will download the embedding model (approx 100MB). This might take a few seconds.
- **Logs**: Check the editor's MCP logs if connection fails.
