memory vs vectorize-mcp-server
Side-by-side comparison to help you pick between these two MCP servers.
memory by modelcontextprotocol | vectorize-mcp-server by vectorize-io | |
|---|---|---|
| Stars | ★ 85,748 | ★ 106 |
| 30d uses | — | — |
| Score | 77 | 47 |
| Official | ✓ | — |
| Categories | Knowledge GraphAI / LLM ToolsProductivity | AI / LLM ToolsKnowledge GraphOther |
| Language | TypeScript | JavaScript |
| Last commit | this month | this month |
memory · Summary
An MCP server implementing persistent memory using a local knowledge graph for AI models to remember user information across chats.
vectorize-mcp-server · Summary
Vectorize MCP server enables vector search, text extraction, and deep research through the Model Context Protocol.
memory · Use cases
- Personalizing AI assistant interactions by remembering user preferences, history, and relationships
- Building context-aware chat applications that maintain conversation history
- Creating knowledge bases that persist across AI model sessions
vectorize-mcp-server · Use cases
- Retrieving relevant documents based on semantic search queries
- Converting PDFs and other documents to structured Markdown format
- Performing deep research with web search integration
memory · Install
Installation
Claude Desktop
Add to your claude_desktop_config.json:
{
"mcpServers": {
"memory": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-memory"
]
}
}
}VS Code
Use one-click installation buttons or manually configure in .vscode/mcp.json:
{
"servers": {
"memory": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-memory"
]
}
}
}Docker
{
"mcpServers": {
"memory": {
"command": "docker",
"args": ["run", "-i", "-v", "claude-memory:/app/dist", "--rm", "mcp/memory"]
}
}
}vectorize-mcp-server · Install
Installation
Running with npx
export VECTORIZE_ORG_ID=YOUR_ORG_ID
export VECTORIZE_TOKEN=YOUR_TOKEN
export VECTORIZE_PIPELINE_ID=YOUR_PIPELINE_ID
npx -y @vectorize-io/vectorize-mcp-server@latestClaude Desktop Configuration
Add to your claude_desktop_config.json:
{
"mcpServers": {
"vectorize": {
"command": "npx",
"args": ["-y", "@vectorize-io/vectorize-mcp-server@latest"],
"env": {
"VECTORIZE_ORG_ID": "your-org-id",
"VECTORIZE_TOKEN": "your-token",
"VECTORIZE_PIPELINE_ID": "your-pipeline-id"
}
}
}
}