Provides a privacy-first adaptive review engine with local SQLite storage, enabling item creation, due review retrieval, grading, and statistics via MCP tools.
Knowledge graph for token-efficient code reviews. Builds a structural map of your codebase with Tree-sitter, tracks changes incrementally, and gives AI agents precise context via MCP tools. Features fixed multi-word search, qualified call resolution, dual-mode embedding (ONNX local + LiteLLM cloud), and output pagination.
Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.
Analyzes GitLab group projects to extract purpose, I/O, dependencies, and database tables, serving this knowledge via MCP tools and a read-only HTML visualization.
Enables personal knowledge management through Claude Desktop, allowing users to capture thoughts, connect ideas, and reflect on thinking changes via natural conversation.
Local-first MCP server that extracts structured knowledge from markdown notes into SQLite with full-text search, enabling AI coding tools to retrieve relevant context offline at zero cost.
MCP server that connects AI agents to Google NotebookLM, enabling natural language interaction with notebooks, including Q&A, source ingestion, and audio overview generation.
Self-improving, verifiable memory for AI coding agents. Learns how you work, stops repeating mistakes, models each project, recalls the right lesson at the right moment. Every memory is signed and tamper-evident. Local-first.
An MCP server for the Zotero Web API v3 that lets you search, read, and write items, collections, tags, and notes in a Zotero library, supporting literature-review workflows.
Semantic memory for AI builders: capture the tacit engineering know-how that never reaches your docs, recall it the moment it applies. Built in Rust on Postgres and pgvector.
Local-first external brain for Claude Code, Codex, and any MCP client. Stores decisions, entities, and session artifacts in one SQLite file and exposes MCP tools for
recall, page, promote, review, graph-query, and source-status.
Helps capture professional achievements using the STAR method through iterative interviews. Generates period summaries and performance review self-assessments.