Graphiti Mcp Pro

Name: Graphiti Mcp Pro
Author: itcook

@itcook

Repository

About Graphiti Mcp Pro

Base on Graphiti, Enhanced Core Capabilities, Broader AI Model Compatibility, and Comprehensive Management UI.

#memory #graphiti #ai #management

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "graphiti_pro": {
      "transport": "http",
      "url": "http://localhost:8082/mcp"
    }
  }
}

Tools

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Overview

What is Graphiti Mcp Pro?

Graphiti Mcp Pro is an enhanced memory repository MCP service and management platform built on Graphiti, a framework for temporally‑aware knowledge graphs designed for AI agents in dynamic environments. It adds asynchronous parallel processing, broader AI model compatibility, and a comprehensive visual Web UI for managing the service.

How to use Graphiti Mcp Pro?

Deploy via Docker Compose (recommended) by cloning the repository, optionally configuring the .env file, then running docker compose up -d; access the management interface at http://localhost:6062. For manual installation, ensure Python 3.10+, uv, Node.js 20+, Neo4j 5.26+, and an AI model service are available, then run uv sync, configure .env, and start the service with uv run main.py -m (management backend enabled) or uv run main.py (MCP only). The frontend can be built separately using pnpm in the manager/frontend directory.

Key features of Graphiti Mcp Pro

Asynchronous parallel processing (up to 5 tasks per group)
Four new MCP tools for managing add_memory tasks
Unified configuration management with backend override
Broader model compatibility via the instructor library
Separated model configuration for LLM, small LLM, and embedding
Full management platform with real‑time monitoring and logs

Use cases of Graphiti Mcp Pro

Building context‑aware AI applications that require dynamic, temporal knowledge graphs
Managing distinct developer projects by grouping memories under different group IDs
Performing historical queries on incremental data without full graph recomputation
Combining different AI models (e.g., large + small LLMs) for efficient entity and relationship extraction

FAQ from Graphiti Mcp Pro

Does the management backend have authentication?

No, the management backend does not implement authorization. Do not expose the service on public servers.

What transport protocol does Graphiti Mcp Pro use?

Only the streamable-http transport protocol is supported; stdio and sse support from the original project has been removed.

How does configuration work when the management backend is enabled?

When the management backend is enabled, parameters in the .env file only take effect on the first startup; subsequent configurations are managed through the backend database.

Can I use models like DeepSeek, Qwen, or local models?

Yes, through integration with the instructor library, Graphiti Mcp Pro supports any model that provides an OpenAI‑compatible API, including DeepSeek, Qwen, and models run via Ollama or vLLM.