PluresLM MCP Service

Distributed vector memory service for AI assistants powered by PluresDB.

PluresLM MCP provides persistent vector memory with P2P synchronization across devices. Built on PluresDB for distributed data and Model Context Protocol for AI tool integration.

Features

• 🧠 Persistent vector memory - Semantic search across conversation history

• 🌐 P2P synchronization - Share memories across devices via Hyperswarm

• 🔧 MCP protocol - Standard interface for AI assistant integration

• 🚀 Multiple transports - stdio, SSE/HTTP for different deployment needs

• 📦 Zero-knowledge - No central servers, encrypted P2P mesh

• 🛠️ Project indexing - Ingest codebases for context-aware assistance

Related MCP server: Recall

Quick Start

Local Development (stdio)

npm install
npm run build

# Set PluresDB topic (generate with: openssl rand -hex 32)
export PLURES_DB_TOPIC="your-64-char-hex-topic-key"

# Start stdio MCP server
npm start

Remote Service (HTTP/SSE)

# Configure for HTTP transport
export MCP_TRANSPORT=sse
export PORT=3001
export HOST=0.0.0.0
export PLURES_DB_TOPIC="your-topic-key"

# Start HTTP service
npm start
# → Serving on http://0.0.0.0:3001/sse

Configuration

Environment Variables

OpenClaw Integration

Local (stdio):

{
  "mcpServers": {
    "pluresLM": {
      "command": "node", 
      "args": ["path/to/pluresLM-mcp/dist/index.js"],
      "env": {
        "PLURES_DB_TOPIC": "your-topic-key"
      }
    }
  }
}

Remote (SSE):

{
  "mcpServers": {
    "pluresLM": {
      "transport": {
        "type": "sse",
        "url": "http://memory-service:3001/sse" 
      }
    }
  }
}

Architecture

PluresDB Backend

PluresLM v2.0+ uses pure PluresDB for storage and synchronization:

• No SQLite dependencies - Distributed-first design

• Hyperswarm P2P mesh - Direct device-to-device sync

• Embedded vector search - Cosine similarity in-memory

• Conflict-free replication - CRDTs for distributed consistency

Transport Options

1. stdio (default) - Process pipes for local OpenClaw integration

2. sse - Server-Sent Events over HTTP for remote/clustered deployments

Memory Sync

All devices sharing the same PLURES_DB_TOPIC automatically sync memories:

# Device 1
export PLURES_DB_TOPIC="abc123..." 
npm start  # Stores memories locally

# Device 2  
export PLURES_DB_TOPIC="abc123..."  # Same topic
npm start  # Automatically receives Device 1's memories

Tools

PluresLM MCP exposes these tools for AI assistants:

• pluresLM_store(content, tags?, category?, source?) - Store new memory

• pluresLM_search(query, limit?, minScore?) - Semantic search

• pluresLM_forget(id? | query?, threshold?) - Delete memories

• pluresLM_index(directory, maxFiles?, category?, tags?) - Index codebase

• pluresLM_status() - Database stats + sync status

• pluresLM_profile() - User profile data

Deployment

Connect-msWork Fleet

For enterprise deployments across multiple OpenClaw instances:

# Memory service (dedicated server)
docker run -p 3001:3001 -e MCP_TRANSPORT=sse plures/pluresLM-mcp

# Worker instances (point to service)
export MCP_TRANSPORT=sse
export PLURES_LM_SERVICE_URL=http://memory-service:3001/sse

High Availability

# Multiple services with shared PluresDB topic
docker-compose up -d  # Load balancer → N service instances

Migration from v1.x

PluresLM v2.0 is a breaking change from SQLite-based v1.x:

What Changed

• ❌ Removed: All SQLite/better-sqlite3 dependencies

• ✅ Added: PluresDB distributed storage

• ✅ Added: P2P mesh synchronization

• ✅ Added: SSE/HTTP transport option

• 🔄 Changed: Tool names (memory_* → pluresLM_*)

• 🔄 Changed: Configuration (file paths → topic keys)

Migration Path

1. Export v1.x data: pluresLM_export_bundle

2. Deploy v2.0 with PluresDB topic

3. Import data: pluresLM_import_bundle

Note: Direct file migration not supported due to schema differences.

License

Dual-licensed under BSL-1.1 and MIT. You may choose either license at your option.

Links

• PluresDB - Distributed database engine

• Model Context Protocol - AI tool standard

• OpenClaw - AI assistant platform