Sandra: open-source persistent graph memory MCP for Claude
Claude forgets everything between sessions. Project memory and CLAUDE.md help but don't scale to structured knowledge. Sandra solves this: a graph + vector memory backend with a native MCP server, open-sourced under MIT. It started 15 years ago as EverdreamSoft's internal memory layer (still powers Spells of Genesis in production).
Key features
- Persistent memory across sessions as a graph (subject, verb, target)
- Claude reads and writes through MCP tools, no manual updates
- Exact, fuzzy, and semantic search exposed as MCP tools
- Long-text storage per entity (notes, full documents) on top of structured refs
Concrete example
Tell Claude in one session: "we're building Phoenix with Marie and Tom, it runs on Postgres". A week later in a fresh chat: "who's on Phoenix?" → Marie and Tom. Tom opens his own Claude session connected to the same Sandra instance: "what DB does Marie's project use?" → Claude traverses Marie → works_on → Phoenix → uses → Postgres. Same graph, any teammate, no manual handoff.
Vector memory typically returns the original sentence as a chunk and loses the link when queried through a different path, plus most setups are per-user only.
Setup (2 minutes)
git clone https://github.com/everdreamsoft/sandra && cd sandra
docker compose up -d
claude mcp add sandra --transport http --url http://127.0.0.1:8090/mcpThen ask Claude to remember something, query it, or build the graph as you talk.
Benchmarks
Sandra scores 0.89 on Structured Recall Bench (130 deterministic questions, no LLM judge). Vector stores cluster between 0.25 and 0.48 on the same bench. Methodology and raw JSON: benchmark details.
Who is this for?
Developers using Claude AI coding agents who need persistent, structured, multi-user memory across sessions.
📖 Read the full source: r/ClaudeAI
👀 See Also
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