Skip to content
Memory MCP Server logo

Memory MCP Server

UnclaimedEditor reviewed

Persistent memory MCP server, your AI remembers context across conversations

Visit Website

TL;DR - Memory MCP Server

  • Persistent memory for AI assistants across conversation sessions
  • Stores entities and relationships in a local knowledge graph
  • No cloud dependency, data stays on your machine
Pricing: Free forever
Best for: Individuals & startups

What Users Say About Memory MCP Server

Memory MCP is Anthropic's reference server for giving agents persistent memory across sessions — a knowledge graph that the agent updates as it works. Users like that it's genuinely free, local, and model-agnostic. The complaints: the graph model is simple (entities + relations + observations) and power users wanting richer memory schemes often graduate to custom solutions.

Highlights

  • Official and maintained by Anthropic — free to run locally
  • Simple knowledge graph: entities, relations, observations
  • Persists state across sessions and agent restarts
  • Any MCP-compatible client can read/write the same graph
  • Zero API costs — purely local storage

Limitations

  • Graph model is simple — not a full vector DB or RAG stack
  • No built-in observability for memory drift or conflicting entries
  • No UI — you inspect the graph through the agent or raw JSON
  • No built-in pruning; old memories accumulate and consume context
  • Power users often graduate to custom vector stores for richer recall

Best for: Simple agent workflows that need long-term state — chat assistants, project agents, task managers. The lightweight answer when you don't want to run Pinecone or Qdrant. For production RAG use Supabase vector or Qdrant instead.

Editorial synthesis from industry coverage, product docs, and early user reports

Pros & Cons

Pros

  • AI remembers project decisions and preferences between sessions
  • Privacy-friendly, no data leaves your machine

Cons

  • Memory is local, not shared across devices
  • Graph can grow large over time without cleanup

Key Features

Entity storage with relationshipsCross-session persistenceKnowledge graph queriesLocal-only storage

Pricing Plans

Open Source

Free

  • Full source code access
  • Community support
  • Self-hosted

What is Memory MCP Server?

Editorial review
Memory MCP Server gives your AI persistent memory across conversations using a local knowledge graph. Store entities, relationships, and project context that persists between sessions. No cloud, everything stored locally.

Reviews

Be the first to review Memory MCP Server

Your take helps the next buyer. Verified LinkedIn reviewers get a badge.

Write a review

Best Memory MCP Server Alternatives

Top alternatives based on features, pricing, and user needs.

View full list →

Explore More

Memory MCP Server FAQ

What does Memory MCP Server do?

Memory MCP Server gives AI agents persistent memory across conversations using a local knowledge graph. Agents can store entities, relationships, and observations that survive between sessions — solving the problem of AI forgetting everything when a conversation ends.

How does Memory MCP Server store data?

It uses a local JSON-based knowledge graph with entities (people, projects, concepts), relations (links between entities), and observations (facts about entities). The data persists in a file on your filesystem.

Is Memory MCP Server free?

Yes, completely free and open source under the MIT license. It is part of the official MCP reference server collection. No API keys, accounts, or external services needed.

What are good use cases for Memory MCP Server?

Storing user preferences across sessions, maintaining project context (tech stack, conventions, team members), tracking meeting notes and decisions, and building up domain knowledge that the AI can reference later.

How do I configure Memory MCP Server?

Add npx -y @anthropic-ai/memory-mcp to your MCP client config. Optionally set the MEMORY_FILE_PATH environment variable to control where the knowledge graph JSON file is stored. Default location is in the package directory.

Source: github.com

Guides & Articles