CLI tool to generate code context files
Config-driven AI context sync tool for rules and skills across coding agents
useVyre AI context — inject into LLM system prompts to eliminate UI hallucinations
Core indexing engine for AI Context
Project templates for ai-context-kit
CLI tool for indexing codebases with AI Context
AI context window cost analysis - detect fragmented code, deep import chains, and expensive context budgets
Crowdin AI Context Harvester CLI
SharkCraft AI context builder: token-budgeted relevance retrieval for tasks.
Repository hygiene analyzer — multi-language AI context efficiency
AI context infrastructure for coding agents — keeps CLAUDE.md, Cursor rules, and skills in sync as your codebase evolves
Txa_MCP - Professional MCP Server & CLI for Local AI Context Management
> Token-budgeted AI context builder and `claude.md` / `AGENTS.md` generator.
Model Context Protocol integration for AI Context
Persistent AI Context Standard — project DNA for AI. IANA-registered. Anthropic-approved.
Semantic duplicate pattern detection for AI-generated code - finds similar implementations that waste AI context tokens
AI context snippets for BlockSlides (v1 atoms, examples, schemas, types)
Simple AI Context for Better Code Generation - Persistent context system for AI coding assistants
A dotctx CLI for repo-local AI context packs.
Local developer cockpit for projects, processes, logs, ports, Git state, and AI context.
Zero-dependency AI context engine — 97% token reduction. No npm install. Runs on Node 18+.
vexp MCP server — AI context tools for coding agents
Custom Linear MCP Server with optimized GraphQL queries for AI context efficiency.
SiderMem CLI Client - Manage your AI context from the terminal
Extract timeline and memory from AI agent sessions (Claude Code, Codex, Gemini)
Operator CLI + MCP server: canonical corpus first, optional semantic index second (Claude Code, Codex, Gemini)
FAF (Foundational AI-context Format) — Project DNA for any AI. IANA-registered application/vnd.faf+yaml.
Parser and tools for .faf files — Foundational AI-context Format
Engine for FAF (Foundational AI-context Format) — parsing, scoring, compilation
Rust SDK for FAF (Foundational AI-context Format) - IANA-registered application/vnd.faf+yaml
MCP server for FAF (Foundational AI-context Format) — Model Context Protocol integration
WASM runtime for FAF (Foundational AI-context Format) — browser and edge computing
FAFb binary format for FAF (Foundational AI-context Format) — IANA-registered application/vnd.fafb
CLI for FAF (Foundational AI-context Format) — Project DNA for any AI
Radio Protocol for FAF — broadcast AI context once, every tool receives
Radio Protocol client for FAF — broadcast AI context once, all tools receive. Client SDK for mcpaas.live.
rails-ai-context turns your running Rails app into the source of truth for AI coding assistants. Instead of guessing from training data or stale file reads, agents query 38 live tools (via MCP server or CLI) to get your actual schema, associations, routes, inherited filters, conventions, and test patterns. Semantic validation catches cross-file errors (wrong columns, missing partials, broken routes) before code runs — so AI writes correct code on the first try. Auto-generates context files for Claude Code, Cursor, GitHub Copilot, OpenCode, and Codex CLI. Works standalone or in-Gemfile.
Interactive rake tasks to generate context files for AI coding assistants (Claude, Cursor, Windsurf, Codex, llm.txt). Uses RubyLLM to analyze your codebase and create platform-specific context that helps AI understand your project.
context_spook is a library that collects and organizes project information to help AI assistants understand codebases better.
ace-git gives developers and coding agents focused git context commands and guided workflows for rebases, pull requests, and commit reorganization, with smart diff output and Git 2.23+ guardrails.
Memoflow captures git-backed development context and exposes a lightweight query API for AI assistants.
Rails-AI-Bridge introspects your Rails application and exposes structure to AI assistants via static context files and a live Model Context Protocol (MCP) server. It classifies Active Record models semantically (Core, Join, Supporting), optionally surfaces non-ActiveRecord Ruby classes under app/models (tagged POJO/Service), and integrates with editors and assistants such as Claude, Gemini, Cursor, and Windsurf.
Superkick wraps AI coding CLIs in a PTY proxy and injects CI results, PR reviews, and other external context — right when the agent is ready to hear it.
A CLI tool that analyzes source code to extract contextual information for translation keys, improving translation quality with AI-powered analysis.
Ruby client library for integrating with Model Context Protocol (MCP) servers to access and invoke tools from AI assistants
Build AI agents with declarative DSL and Model Context Protocol support
RLM.rb is a Ruby runtime spine for Recursive Language Models. It runs bounded, typed, auditable AI jobs over files, records, and application context. RLM.rb includes RubyLLM provider access, a dspy.rb signature adapter, the recursive prompt loop, file/context mounting, recursive sub-LM calls, typed final output, budget controls, trace events, and a best-effort trace_store hook.
Claude Swarm enables you to run multiple Claude Code instances that communicate with each other via MCP (Model Context Protocol). Create AI development teams where each instance has specialized roles, tools, and directory contexts. Define your swarm topology in simple YAML and let Claude instances collaborate across codebases. Perfect for complex projects requiring specialized AI agents for frontend, backend, testing, DevOps, or research tasks.
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