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Security-hardened NotebookLM MCP with post-quantum encryption (ML-KEM-768), GDPR/SOC2/CSSF compliance, and 14 security layers. Query Google's Gemini-grounded research from Claude and AI agents.
Temporal knowledge graph for codebases. Captures decision traces, links test failures to code changes, learns co-edit patterns, predicts regression risk, and enforces learned constraints at the edit boundary via a PreToolUse hook. 22 MCP tools, 9 SQLite databases with FTS5, supports Python/TypeScript/JavaScript/Solidity/Go/Rust/Java. Install via `pip install world-model-mcp`.
Compiles saved YouTube videos, podcasts, articles, PDFs, and Notion/Obsidian notes into a persistent, semantically searchable knowledge base any AI can query over MCP.
Self-hosted memory and governance layer for AI coding agents. 28 MCP tools with structured knowledge capture, hybrid search (semantic + BM25 + cross-encoder reranking), behavioral documentation nudges, cold-start codebase analyzer, and git-native storage. Single Docker container, zero cloud dependencies.
Local-first semantic memory server with hybrid search, plain Markdown storage, MLX or CPU embeddings, contradiction detection, time-travel history, synthesis, and cross-machine git sync.
Persistent graph memory for AI agents. Drop a conversation turn in via `observe_conversation()` and facts are auto-extracted, stored as typed graph nodes with local semantic embeddings (no API key). Supports temporal queries ("what did we decide last week?"), conflict detection, and context priming. One-command setup with `waggle-mcp init`. SQLite locally, Neo4j in production.
Ingest anything from Slack, Discord, websites, Google Drive, Linear or GitHub into a Graphlit project - and then search and retrieve relevant knowledge within an MCP client like Cursor, Windsurf or Cline.
Two-tier memory with hot cache (instant injection) and cold semantic search. Auto-promotes frequently-used patterns, extracts knowledge from Claude outputs, and organizes via knowledge graph relationships.
Memory manager for AI apps and Agents using various graph and vector stores and allowing ingestion from 30+ data sources
Semantic knowledge graph for Obsidian. Three modes (pure graph / semantic classification / strict hierarchy), local embeddings, sign classification via cosine similarity to user-defined cores, bottom-up core_mix aggregation, semantic bridge discovery, and drift detection. `pip install nouz-mcp`
Persistent semantic memory for AI agents. SQLite-backed, local-first, zero config. Semantic search via Ollama embeddings (nomic-embed-text) with keyword fallback. remember, recall, history, forget, and stats tools. Works with Claude Desktop, Cursor, and any MCP client.
Local-first agent memory: a plain-Markdown Obsidian vault is the source of truth, with a rebuildable DuckDB index for hybrid BM25 + vector + graph recall. Non-lossy capture with secret redaction; works across Claude Code, Codex, Cursor, and any MCP host. `uvx agentcairn`