MCP server for semantic memory and codebase search with LanceDB and Voyage AI embeddings
npm install @indokq/memory-mcp~/.claude.json):
json
{
"mcpServers": {
"memory": {
"command": "npx",
"args": ["-y", "@indokq/memory-mcp"],
"env": {
"VOYAGE_API_KEY": "your-voyage-api-key"
}
}
}
}
`
Tools
$3
Search past context and memories by semantic similarity. Also searches indexed codebase files.
Parameters:
- query (string, required): Search query text
- top_k (number, optional): Number of results to return (default: 5)
- threshold (number, optional): Minimum similarity threshold (default: 0.4)
- layers (string[], optional): Filter by memory layers (raw, consolidated, meta)
- project (string, optional): Filter by project name
- include_codebase (boolean, optional): Also search indexed codebase files (default: true)
$3
Store important information as a memory for future retrieval.
Parameters:
- content (string, required): Content to store as memory
- tags (string[], optional): Tags for categorization
- importance (number, optional): Importance score 0-1 (default: 0.5)
- project (string, optional): Project name
- layer (enum, optional): Memory layer - "raw", "consolidated", or "meta" (default: raw)
$3
Get recurring coding patterns and preferences from past sessions.
Parameters:
- project (string, optional): Filter patterns by project
$3
Get context about a specific project including structure, tech stack, and recent decisions.
Parameters:
- project (string, required): Project name to get context for
$3
Index codebase files for semantic search. Scans files and generates embeddings.
Parameters:
- path (string, optional): Root path to index (defaults to current directory)
- patterns (string[], optional): Glob patterns for files to include
- ignore (string[], optional): Glob patterns for files to ignore
Configuration
$3
- VOYAGE_API_KEY (required): Your Voyage AI API key
$3
All data is stored locally in ~/.claude/memory/lancedb/.
Models Used
- Embeddings: voyage-4-lite (1024 dimensions)
- Reranking: rerank-2.5-lite`