Memento v1.0: Persistent Memory MCP Server for Claude Code with 17 Tools

✍️ OpenClawRadar📅 Published: March 24, 2026🔗 Source
Memento v1.0: Persistent Memory MCP Server for Claude Code with 17 Tools
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Memento v1.0 is a persistent memory MCP server for Claude Code that gives AI coding agents long-term memory across sessions. The tool runs entirely locally with no cloud dependencies, API keys, or telemetry.

Core Features

The server ships with 17 MCP tools: save, recall, search, forget, list, export, import, ingest, index, migrate, compact, stats, profile, related, session start, session summary, and health.

Search Capabilities

  • Vector search: Uses cosine similarity with HNSW index to find memories by meaning
  • Keyword search: Full BM25 implementation (same algorithm as Elasticsearch) for exact term matching
  • Hybrid search: Combines 70% vector + 30% BM25 scoring, which the creator uses daily

Intelligent Memory Management

  • Contradiction detection: Automatically creates supersedes relationships when you change decisions (e.g., "we use PostgreSQL" → "switched from PostgreSQL to CockroachDB") and deprioritizes old information
  • Importance scoring: Explicit saves > auto-captures, decisions > conversation, with 347-day exponential decay so recent context surfaces first
  • Knowledge graph: Extracts file paths, functions, classes, packages, URLs, and environment variables from every memory
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Visualization and API

memento serve starts a local server at localhost:7007 that provides:

  • D3.js force-directed graph visualization with nodes colored by tag and edges showing relationships
  • REST API mirroring all 17 tools

Production Features

  • Circuit breaker for fault tolerance
  • Write-ahead log for crash recovery
  • LRU cache for embeddings

IDE and Browser Integration

  • Multi-IDE support: Claude Code, Cursor, Windsurf, OpenCode with shared memory store across all four
  • Chrome extension: Right-click any page or selection to save it directly to memory

Usage Data

During v1.0 development, Memento captured 2,191 memories across 27 sessions: 1,905 from auto-capture hooks, 206 from session summaries, and 79 explicit saves. This created 53MB of searchable engineering context.

Setup and Resources

Setup command: npx memento-memory setup

  • GitHub: https://github.com/sanathshetty444/memento
  • Documentation: https://sanathshetty444.github.io/memento/
  • Full writeup: https://medium.com/@sanathshetty444/it-remembered-9e7d10f444ff

📖 Read the full source: r/ClaudeAI

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👀 See Also

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