"Graphite" matching MCP servers:

A read-only MCP server that lets you search current and historical facts from a time-indexed knowledge graph derived from a folder of Markdown/text documents, with verification against original sources. It exposes tools for status, fact search, history search, and revision lookup while keeping document insertion and modification to the CLI.

Enables storing and querying memories in a Neo4j knowledge graph with automatic entity extraction. Supports adding episodes, searching entities and relationships, and managing graph data through natural language.

Local-first temporal knowledge graph with six read-only MCP retrieval tools. Supports Ollama and embedded LadybugDB; additions use a separate CLI proposal queue with human approval and explicit application.

A Model Context Protocol server that provides Claude CLI with a Graphiti knowledge-graph memory backed by Neo4j, featuring synchronous writes and no silent ingestion failures.

Enables AI assistants to build and query temporally-aware knowledge graphs from conversations and data. Supports adding episodes, searching entities and facts, and maintaining persistent memory across interactions.

A temporally-aware knowledge graph MCP server for AI agents, enabling episodic ingestion, entity management, and semantic search with support for multiple LLM and embedding providers.

A framework for building and querying temporally-aware knowledge graphs that allows AI assistants to interact with graph capabilities through the Model Context Protocol.

Enables AI agents to build real-time knowledge graphs using Zep's Graphiti memory, persisting context in Neo4j.

An enhanced memory repository MCP service that builds and queries temporally-aware knowledge graphs from user interactions and data. Features asynchronous parallel processing, task management, broader AI model compatibility, and a comprehensive visual management interface.

Enhanced memory repository MCP service that enables building and querying temporally-aware knowledge graphs from user interactions and enterprise data. Features asynchronous processing, task management tools, multi-model compatibility, and a comprehensive visual management interface.

Enables AI assistants to build and query temporally-aware knowledge graphs from conversations and data, maintaining persistent memory of entities, relationships, and facts across interactions.

Enables AI agents to manage and query a temporally-aware knowledge graph memory, supporting episode tracking, entity relationships, and semantic search via MCP tools.

Gives AI agents persistent memory with bi-temporal tracking, automatically extracting entities from natural language and enabling time-travel queries to understand facts as they existed at any point in history.