memstate-ai/memstate-mcp
Platform-specific configuration:
{
"mcpServers": {
"memstate-mcp": {
"command": "npx",
"args": [
"-y",
"memstate-mcp"
]
}
}
}Add the config above to .claude/settings.json under the mcpServers key.
[](https://www.npmjs.com/package/@memstate/mcp) [](https://opensource.org/licenses/MIT) [](https://modelcontextprotocol.io) [](https://nodejs.org)
Versioned memory for AI agents. Store facts, detect conflicts, and track how decisions change over time — exposed as a hosted MCP server.
---
| | RAG (most other memory systems) | Memstate AI | |---|---|---| | Token usage per conversation | ~7,500 | ~1,500 | | Agent visibility | Black box | Full transparency | | Memory versioning | None | Full history | | Token growth as memories scale | O(n) | O(1) | | Infrastructure required | Yes | None — hosted SaaS |
Other memory systems dump everything into your context window and hope for the best. Memstate gives your agent a structured, versioned knowledge base it navigates precisely — load only what you need, know what changed, know when facts conflict.
---
We built an open-source benchmark suite that tests what actually matters for agent memory: can your system store facts, recall them accurately across sessions, detect conflicts when things change, and maintain context as a project evolves?
Both systems were tested under identical conditions using the same agent (Claude Sonnet 4.6, temperature 0), the same scenarios, and the same scoring rubric.
| Metric | Memstate AI | Mem0 | Winner | |--------|:-----------:|:----:|--------| | Overall Score | 69.1 | 15.4 | Memstate | | Accuracy (fact recall) | 74.1 | 12.6 | Memstate | | Conflict Detection | 85.5 | 19.0 | Memstate | | Context Con
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