Memvid MCP Server

Unofficial Model Context Protocol (MCP) server interface to Memvid - a video-frame memory system for AI agents.

What is Memvid?

Memvid is a memory layer for AI agents that stores knowledge as compressed "Smart Frames" in a single .mv2 file (similar to how video stores frames). This approach provides:

• 10x more storage efficiency than traditional vector databases
• Sub-5ms memory access times
• Append-only, crash-safe storage with time-travel capabilities
• Single portable file containing data, embeddings, search structure, and metadata
• No external database or infrastructure required

Features

• Persistent long-term memory for AI agents
• Semantic search with natural language queries
• Instant retrieval from a single portable file
• Serverless architecture - no database infrastructure needed
• Model-agnostic - works with any LLM that supports MCP

Installation

From Cargo (Rust)

cargo install --git https://github.com/mystique09/memvid-mcp.git

From Source

git clone https://github.com/mystique09/memvid-mcp.git
cd memvid-mcp
cargo build --release
# The binary will be at target/release/memvid-mcp.exe (Windows) or target/release/memvid-mcp (Linux/Mac)

Configuration

Continue

Add to your mcpServers/new-mcp-server.yaml:

mcpServers:
  - name: Memvid MCP
    type: stdio
    command: memvid-mcp

Claude Desktop

Add to your Claude Desktop config (claude_desktop_config.json):

{
  "mcpServers": {
    "memvid": {
      "command": "memvid-mcp",
      "env": {}
    }
  }
}

Cline (VS Code Extension)

Add to your Cline settings:

{
  "mcpServers": [
    {
      "name": "memvid",
      "command": "memvid-mcp"
    }
  ]
}

Available Tools

Tool	Purpose	Description
ping	Health check	Returns "pong" to verify server is running
add_chunks	Store memory	Stores text chunks as memory frames with semantic embeddings. Returns count and sequence IDs
search	Query memory	Searches using natural language. Returns relevant chunks ranked by semantic similarity

Usage Examples

Store Chunks

Use the add_chunks tool to store information:
Add chunks ["Meeting discussed Q1 planning", "Action item: Review API integration", "Decision: Use Memvid for memory"]

Search Memory

Use the search tool with natural language queries:
Search for "Q1 planning" with top_k=5 and snippet_chars=200

Health Check

Ping to verify server is responsive:
Ping

Storage

All data is stored in memvid.mv2 in the current working directory. This is a single, portable file that includes:

• Compressed frames
• Full-text index
• Vector index
• Timeline metadata

The .mv2 file can be shared, versioned, and backed up like any other file.

Development

Build

cargo build

Run (Development)

cargo run

Test with MCP Client

# Create test requests
echo '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2024-11-05","capabilities":{"tools":{}},"clientInfo":{"name":"test","version":"1.0.0"}}}' | cargo run

Requirements

• Rust 1.85.0+
• memvid-core crate (included as dependency)

Learn More

• Memvid Documentation
• Memvid GitHub
• Model Context Protocol Spec

License

Apache License 2.0

Contributing

Contributions welcome! Please feel free to submit a Pull Request.