Linter for AI agent context files and MCP configs: CLAUDE.md, AGENTS.md, .cursorrules, .mcp.json - catches broken paths, wrong commands, leaked secrets

Model Context Protocol adapter for ai-agent-context. Exposes the repository knowledge graph to MCP clients over stdio. Contains no business logic of its own.

Cadet Token Saver — an orchestration + measurement layer that reduces AI-agent context consumption.

CLI tool for automating AI agent context setup in projects

Cadet Brainstem — an orchestration + measurement layer that reduces AI-agent context consumption.

Keep your AI agent context small and cheap by managing tool bloat and large outputs.

Core of ai-agent-context: repository knowledge graph, architecture detection, incremental scanning, deterministic .agent/ serialization. Local-first, zero runtime dependencies, no LLM required.

Decide what to keep, drop, or summarize in AI agent context: by recency (the default), keyword overlap, or Jev's relevance scores (opt-in).

The file protocol for AI agent context. Encrypted, signed, peer-to-peer.

A Model Context Protocol server for persistent project-specific AI agent context.

CLI tool for automating AI agent context setup in projects

Zero-knowledge encrypted sync for AI agent context

Lint your AGENTS.md, CLAUDE.md, and AI agent context files. Catch stale refs, dead commands, and token waste.

Git-native context layer for AI coding agents: scan a repository into a structured, versionable .agent/ knowledge layer and query it (CLI + programmatic API).

A git-centric developer-workflow assistant CLI: PR descriptions, commit messages, branch names, project context briefs, and AI agent context files.

MCP server for AI agent context caching

Semantic clustering mindmap for AI agent context management

Generate and maintain AI agent context files for your codebase

Linter, profiler, and coverage for AI agent context files (AGENTS.md, CLAUDE.md, .cursor/rules, copilot-instructions, .windsurf/rules)

Generate a YAML map of your codebase for AI agent context