Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Vector Memory MCP ServerWhat did we decide about the database schema in our last session?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Vector Memory MCP Server
Semantic memory storage for AI assistants. Store decisions, patterns, and context that persists across sessions.
A local-first MCP server that provides vector-based memory storage. Uses local embeddings and LanceDB for fast, private semantic search.
Features
Local & Private - All embeddings generated locally, data stored in local LanceDB
Semantic Search - Vector similarity search with configurable scoring
Batch Operations - Store, update, delete, and retrieve multiple memories at once
Session Checkpoints - Save and restore project context between sessions
MCP Native - Standard protocol, works with any MCP-compatible client
Quick Start
Prerequisites
Bun 1.0+
An MCP-compatible client (Claude Code, Claude Desktop, etc.)
Install
bun install -g @aeriondyseti/vector-memory-mcpFirst install downloads ML models (~90MB). This may take a minute.
Configure
Add to your MCP client config (e.g., ~/.claude/settings.json):
{
"mcpServers": {
"vector-memory": {
"type": "stdio",
"command": "bunx",
"args": ["--bun", "@aeriondyseti/vector-memory-mcp"]
}
}
}Use
Restart your MCP client. You now have access to:
Tool | Description |
| Save memories (accepts array) |
| Find relevant memories semantically |
| Retrieve memories by ID (accepts array) |
| Update existing memories |
| Remove memories (accepts array) |
| Save session context for later |
| Restore session context |
Usage
Store a memory:
You: "Remember that we use Drizzle ORM for database access"
Assistant: [calls store_memories]Search memories:
You: "What did we decide about the database?"
Assistant: [calls search_memories with relevant query]Session checkpoints:
You: "Save context for next session"
Assistant: [calls store_checkpoint with summary, completed items, next steps]Configuration
Configuration is resolved in order: CLI flags > environment variables > defaults.
CLI Flags
Flag | Alias | Default | Description |
|
|
| Database location (relative to cwd) |
|
|
| HTTP server port |
| Disable the HTTP server |
Environment Variables
Variable | Default | Description |
|
| Database location |
|
| HTTP server port |
Environment variables are useful in MCP client configs where you can't pass CLI flags directly:
{
"mcpServers": {
"vector-memory": {
"type": "stdio",
"command": "bunx",
"args": ["--bun", "@aeriondyseti/vector-memory-mcp"],
"env": {
"VECTOR_MEMORY_DB_PATH": "/home/user/.local/share/vector-memory-mcp/memories.db"
}
}
}
}Development
git clone https://github.com/AerionDyseti/vector-memory-mcp.git
cd vector-memory-mcp
bun install
bun run test # Run all tests
bun run dev # Watch mode
bun run typecheck # Type checkingSee CHANGELOG.md for release history and ROADMAP.md for planned features.
Contributing
Contributions welcome! See issues for areas we'd love help with.
License
MIT - see LICENSE
Built with MCP SDK, LanceDB, and Transformers.js