How do I install the graphiti mcp server?

Use a recorded configuration for your client, replace example credential values and paths, and verify the documented runtime. Restart or reconnect the client, then inspect the available tools.

What credentials does it need?

It reads `NEO4J_URI`, `NEO4J_USER`, `NEO4J_PASSWORD`, `OPENAI_API_KEY`, `MODEL_NAME`, `OPENAI_BASE_URL` from the environment. Store these in your client's env block or a secrets manager — never commit them to a repository — and grant the narrowest scope that still covers your use case.

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Graphiti MCP Server

Graphiti is a framework for building and querying temporally-aware knowledge graphs, specifically tailored for AI agents operating in dynamic

Local serverstdioPython

What is the Graphiti MCP Server?

Graphiti is a framework for building and querying temporally-aware knowledge graphs, specifically tailored for AI agents operating in dynamic environments. Unlike

The short version

Episode Management — Add, retrieve, and delete episodes (text, messages, or JSON data)
Entity Management — Search and manage entity nodes and relationships in the knowledge graph
Search Capabilities — Search for facts (edges) and node summaries using semantic and hybrid search
Group Management — Organize and manage groups of related data with group_id filtering
Graph Maintenance — Clear the graph and rebuild indices

What it needs from you

Ensure you have Python 3.10 or higher installed. 2. A running Neo4j database (version 5.26 or later required) 3. OpenAI API key for LLM operations

More MCP options

Compare MCP servers by category, or browse hosted MCP servers if you prefer an endpoint over a local process.

Maintainer setup documentation.

Recorded tools

Check the linked publisher documentation and your connected client's tool list. Names and availability can vary with the server version and account permissions.

Tool	What it does
add_episode	Add an episode to the knowledge graph (supports text, JSON, and message formats)
search_nodes	Search the knowledge graph for relevant node summaries
search_facts	Search the knowledge graph for relevant facts (edges between entities)
delete_entity_edge	Delete an entity edge from the knowledge graph
delete_episode	Delete an episode from the knowledge graph
get_entity_edge	Get an entity edge by its UUID
get_episodes	Get the most recent episodes for a specific group
clear_graph	Clear all data from the knowledge graph and rebuild indices
get_status	Get the status of the Graphiti MCP server and Neo4j connection

How to install the Graphiti MCP Server

{
  "mcpServers": {
    "graphiti-memory": {
      "transport": "stdio",
      "command": "/Users/<user>/.local/bin/uv",
      "args": [
        "run",
        "--isolated",
        "--directory",
        "/Users/<user>>/dev/zep/graphiti/mcp_server",
        "--project",
        ".",
        "graphiti_mcp_server.py",
        "--transport",
        "stdio"
      ],
      "env": {
        "NEO4J_URI": "bolt://localhost:7687",
        "NEO4J_USER": "neo4j",
        "NEO4J_PASSWORD": "YOUR_NEO4J_PASSWORD",
        "OPENAI_API_KEY": "YOUR_OPENAI_API_KEY",
        "MODEL_NAME": "gpt-4.1-mini"
      }
    }
  }
}

From the project documentation. Replace placeholders and example paths before connecting.

Configuration

Ensure you have Python 3.10 or higher installed. 2. A running Neo4j database (version 5.26 or later required) 3. OpenAI API key for LLM operations

Variable	Description	Required
NEO4J_URI	Declared in the maintainer’s client configuration.	Check documentation
NEO4J_USER	Declared in the maintainer’s client configuration.	Check documentation
NEO4J_PASSWORD	Declared in the maintainer’s client configuration.	Check documentation
OPENAI_API_KEY	Declared in the maintainer’s client configuration.	Yes
MODEL_NAME	Declared in the maintainer’s client configuration.	Check documentation

Example prompts to try

“Use Graphiti to add episode.”
“Use Graphiti to search nodes.”
“Use Graphiti to search facts.”

Frequently asked questions

Graphiti is a framework for building and querying temporally-aware knowledge graphs, specifically tailored for AI agents operating in dynamic environments. Unlike Confirm the tools offered by your installed version in the connected client. Tool availability and permissions depend on the server and account configuration.

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