Customized Graphiti MCP server for brainstorming knowledge graphs with specialized entity types for ideas, themes, stakeholders, constraints, and creative collaboration
Overview
What is Graphiti?
Graphiti is a framework designed for building and querying temporally-aware knowledge graphs, specifically tailored for AI agents operating in dynamic environments. It allows for the integration of user interactions and enterprise data into a coherent, queryable graph.
How to use Graphiti?
To use Graphiti, install the package via pip or poetry, set up a Neo4j database, and configure your environment with the necessary API keys. You can then connect to the database and start adding episodes to the graph.
Key features of Graphiti?
- Real-time incremental updates for dynamic data integration.
- Bi-temporal data model for accurate point-in-time queries.
- Hybrid retrieval methods combining semantic, keyword, and graph-based searches.
- Custom entity definitions for flexible ontology creation.
- Scalable architecture suitable for large datasets.
Use cases of Graphiti?
- Building interactive AI applications that require real-time data updates.
- Facilitating state-based reasoning and task automation for AI agents.
- Querying complex, evolving data with various search methods.
FAQ from Graphiti?
- What is the primary use of Graphiti?
Graphiti is primarily used for dynamic data management and building knowledge graphs for AI applications.
- Is Graphiti open-source?
Yes! Graphiti is open-source and available on GitHub.
- What are the system requirements for Graphiti?
Graphiti requires Python 3.10 or higher and Neo4j 5.26 or higher.