Tools for managing AI agent context and memory
Up-to-date code documentation for LLMs and AI code editors, eliminating outdated or hallucinated API references.
A project template that turns your repository into stable infrastructure for AI-assisted development.
Local code intelligence MCP server and CLI for AI coding agents, providing semantic search and call graph analysis.
MCP server that gives AI coding assistants persistent memory, semantic code search, and live telemetry.
Codebase intelligence layer for AI coding agents: code health, git analytics, dead code detection, and architectural decisions via MCP.
A memory layer for coding agents that stores and retrieves repo context, conventions, and invariants.
An LLM-powered framework for automated repository-level code documentation generation.
Deep code indexing MCP server for AI agents with hybrid FTS5 + embedding search, call graphs, and multi-repo workspaces.
Semantic code graph builder with 45 MCP tools, VS Code extension, and persistent memory for AI agents.
Analyze any codebase using real project signals to generate a structured explanation.
Automate technical documentation generation and maintenance for any codebase using AST parsing and dependency graphs.
Persistent project-scoped knowledge base for deep research findings with progressive disclosure and contrarian-pass investigation.
Convert source code repositories into searchable knowledge bases with MCP support for Claude and Cursor.
Agent-first documentation system that keeps project context compact, current, and routed for coding agents.
Standalone Agent Skills for Exa web search — no MCP server, just an API key.
Headless spreadsheet runtime for AI agents — edit cells, recalculate formulas, persist JSON, and refresh XLSX without Excel.
Local-first hybrid semantic code search with pgvector + Ollama embeddings. CLI, MCP server, and web dashboard for 30+ languages.
Builds a knowledge graph from any codebase with 14 LLM backends, impact analysis, and architecture-aware reasoning.
