An MCP server that uses a knowledge graph to store and recall structured memory for AI models
An MCP server that uses a knowledge graph to store and recall structured memory for AI models
MemoryMesh is a knowledge graph server designed for AI models, with a focus on text-based RPGs and interactive storytelling. It helps AI maintain consistent, structured memory across conversations, enabling richer and more dynamic interactions.
MemoryMesh is a local knowledge graph server that empowers you to build and manage structured information for AI models. While particularly well-suited for text-based RPGs, its adaptable design makes it useful for various applications, including social network simulations, organizational planning, or any scenario involving structured data.
Compare MCP servers by category, or browse hosted MCP servers if you prefer an endpoint over a local process.
Store entities, relations and observations in a local knowledge graph with the reference Memory MCP server.
A structured scratchpad for hard problems — stepwise reasoning with revisions, branches and visible logic.
MCP server for codewiki.google: search repos, fetch wiki docs, ask questions
Persistent AI entity framework with causal memory, emotional state, and identity.
100% local MCP server for semantic code search: AST chunking, hybrid retrieval, code knowledge graph
Engram is a hosted MCP server that provides reliable memory for AI agents: