mirror of https://github.com/samvallad33/vestige.git synced 2026-04-25 00:36:22 +02:00

Sam Valladares 5337efdfa7 Switch embedding model from BGE to nomic-embed-text-v1.5

- Replace BGE-base-en-v1.5 with nomic-embed-text-v1.5
- 8192 token context window (vs 512 for BGE)
- Matryoshka representation learning support
- Fully open source with training data released
- Same 768 dimensions, no schema changes required

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

2026-01-25 03:11:15 -06:00

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Vestige MCP Server

A bleeding-edge Rust MCP (Model Context Protocol) server for Vestige - providing Claude and other AI assistants with long-term memory capabilities.

Features

FSRS-6 Algorithm: State-of-the-art spaced repetition (21 parameters, personalized decay)
Dual-Strength Memory Model: Based on Bjork & Bjork 1992 cognitive science research
Local Semantic Embeddings: nomic-embed-text-v1.5 (768d) via fastembed v5 (no external API)
HNSW Vector Search: USearch-based, 20x faster than FAISS
Hybrid Search: BM25 + semantic with RRF fusion
Codebase Memory: Remember patterns, decisions, and context

Installation

cd /path/to/vestige/crates/vestige-mcp
cargo build --release

Binary will be at target/release/vestige-mcp

Claude Desktop Configuration

Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "vestige": {
      "command": "/path/to/vestige-mcp"
    }
  }
}

Available Tools

Core Memory

Tool	Description
`ingest`	Add new knowledge to memory
`recall`	Search and retrieve memories
`semantic_search`	Find conceptually similar content
`hybrid_search`	Combined keyword + semantic search
`get_knowledge`	Retrieve a specific memory by ID
`delete_knowledge`	Delete a memory
`mark_reviewed`	Review with FSRS rating (1-4)

Statistics & Maintenance

Tool	Description
`get_stats`	Memory system statistics
`health_check`	System health status
`run_consolidation`	Apply decay, generate embeddings

Codebase Tools

Tool	Description
`remember_pattern`	Remember code patterns
`remember_decision`	Remember architectural decisions
`get_codebase_context`	Get patterns and decisions

Available Resources

Memory Resources

URI	Description
`memory://stats`	Current statistics
`memory://recent?n=10`	Recent memories
`memory://decaying`	Low retention memories
`memory://due`	Memories due for review

Codebase Resources

URI	Description
`codebase://structure`	Known codebases
`codebase://patterns`	Remembered patterns
`codebase://decisions`	Architectural decisions

Example Usage (with Claude)

User: Remember that we decided to use FSRS-6 instead of SM-2 because it's 20-30% more efficient.

Claude: [calls remember_decision]
I've recorded that architectural decision.

User: What decisions have we made about algorithms?

Claude: [calls get_codebase_context]
I found 1 decision:
- We decided to use FSRS-6 instead of SM-2 because it's 20-30% more efficient.

Data Storage

Database: ~/Library/Application Support/com.vestige.mcp/vestige-mcp.db (macOS)
Uses SQLite with FTS5 for full-text search
Vector embeddings stored in separate table

Protocol

JSON-RPC 2.0 over stdio
MCP Protocol Version: 2024-11-05
Logging to stderr (stdout reserved for JSON-RPC)

License

MIT

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