Provides repository-aware documentation context, convention checks, API context, and proposed documentation updates through MCP.
Key Features: Repository-aware AI context Convention discovery with citations Documentation impact analysis Connects Scrivener 3 projects to AI clients for editing, analysis, search, and writing support.
Key Features: Scrivener 3 document access and editing Deterministic writing analysis Keyword and offline semantic search Indexes repositories into a local code graph for structural search, call tracing, impact analysis, and architecture exploration.
Key Features: Persistent local code knowledge graph Tree-sitter parsing for 162 languages Hybrid LSP semantic resolution Fetches current, version-aware library documentation and code examples for AI coding agents.
Key Features: Documentation and code example retrieval Version-aware documentation queries Hosted memory server for AI agents with feedback-based ranking, recency fading, and multi-client API key support.
Key Features: Memory write, read, list, feedback, stats, and delete APIs Feedback-driven re-ranking of memories based on helpfulness Recency-based fading of recall relevance Connects MCP clients to an Obsidian vault for on-demand context, search, editing, lesson capture, and git-backed session memory.
Key Features: On-demand Obsidian vault context Full-text and ranked search Markdown file creation and patching Local memory layer indexing coding agent session histories for fast recall and cross-machine sync over SSH.
Key Features: Zero-dependency single binary, fully local operation Search 3.5 GB of session history in ~1.5 ms Supports multiple coding agents via MCP protocol The private, owned conversation-memory layer for AI. Record, transcribe, and search every meeting.
Connects AI assistants to Tencent Lexiang for knowledge search, document editing, file handling, and knowledge-base management.
Key Features: Keyword and semantic vector search Entry and folder management Block-level document editing Local-first screen and audio capture system exposing indexed desktop history to AI agents via MCP.
Key Features: Continuous local screen and audio recording with OCR and transcription MCP tools for content search, frame context, and element inspection Recommended desktop app setup via Settings > Connections Offline MCP memory and task management with semantic recall, knowledge graphs, reminders, and local backups.
Key Features: Local semantic and graph-based memory recall Hebbian strengthening and activation decay Persistent reminders and GTD-style todos Searches a Git-backed collection of verified debugging lessons through local or remote MCP tools.
Key Features: BM25 and SAG-Lite lesson search Git-backed failure-recovery knowledge base MCP tools for searching and retrieving lessons