mind-mem and Memory-Plus

mind-mem
54
Established
Memory-Plus
52
Established
Maintenance 13/25
Adoption 10/25
Maturity 18/25
Community 13/25
Maintenance 2/25
Adoption 13/25
Maturity 24/25
Community 13/25
Stars: 5
Forks: 2
Downloads: 385
Commits (30d): 0
Language: Python
License: Apache-2.0
Stars: 52
Forks: 7
Downloads: 149
Commits (30d): 0
Language: Python
License: Apache-2.0
No Dependents
Stale 6m

About mind-mem

star-ga/mind-mem

Persistent, auditable, contradiction-safe memory for coding agents. Hybrid BM25 + vector retrieval, 19 MCP tools, co-retrieval graph, MIND-accelerated scoring. Zero external dependencies.

Implements shared memory across all MCP-compatible AI agents (Claude Code, Cursor, Windsurf, etc.) via a single SQLite workspace with concurrent-safe WAL mode. Core architecture combines BM25F full-text + vector retrieval with RRF fusion and intent-aware routing, plus a co-retrieval graph using PageRank-style propagation to surface structurally-related blocks. Includes active contradiction detection, drift analysis, and deterministic governance—all Markdown-backed with full audit trails and zero external dependencies.

About Memory-Plus

Yuchen20/Memory-Plus

🧠 𝑴𝒆𝒎𝒐𝒓𝒚-𝑷𝒍𝒖𝒔 is a lightweight, local RAG memory store for MCP agents. Easily record, retrieve, update, delete, and visualize persistent "memories" across sessions—perfect for developers working with multiple AI coders (like Windsurf, Cursor, or Copilot) or anyone who wants their AI to actually remember them.

Built on Google's Embedding API for semantic search, Memory-Plus stores encoded memories locally and supports versioning to track changes over time. It integrates as an MCP server via stdio transport, compatible with VS Code, Cursor, Cline, and other MCP-enabled IDEs, with optional resource-based prompting to control when agents access past context.

Scores updated daily from GitHub, PyPI, and npm data. How scores work