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Enable AI agents to ingest, manage, and semantically search temporal knowledge graphs.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Graphiti FastMCP Server" yet — see the docs or source repo.
Use Graphiti FastMCP Server to ingest the following customer support conversation into a knowledge graph in chronological order, extracting entities and relationships such as user, product, issue, and resolution while preserving the event timeline.
A summary of ingested events and entity relationships, plus a temporal memory structure for later queries.
Using Graphiti FastMCP Server, retrieve all events related to "Customer A" over the past three months, including involved products and issue types, and summarize key changes along a timeline.
A time-ordered event list, related entity network, and a summary of key trends.
Use Graphiti FastMCP Server to semantically search historical cases similar to "permission issues after login" and identify the related entities, resolutions, and final outcomes.
A list of semantically matched cases with a summary of common resolution patterns and outcomes.
Ingest documents into Neo4j to build and query a knowledge graph.
Give AI agents persistent temporal memory and custom tool generation.
Provides an MCP server for RAG and knowledge graph integration.
Connect AI to Graphlit for content access, retrieval, and context automation.
Give LLMs persistent knowledge graph memory with semantic retrieval and contextual recall.
Query a bi-temporal property graph via MCP with auditable temporal reasoning.