Compiles AI agent traces and truns them into reusable context.

Spec-driven development and context engineering for Claude Code, Cursor, Codex, and GitHub Copilot — backed by project context in Git.

Analyze your Claude Code context window, detect wasted tokens, and get pasteable fix commands. Zero API calls

deep, reliable and confidential coding-context

Memory and context manager just works.

AI Badger - Local-first tool that extracts focused repo context for any AI chat (Claude, ChatGPT, Grok, etc.) without wasting tokens on irrelevant files.

Visual planning and context control for shipping big apps with AI coding. Build from scratch or map existing repos. Dossier maps user workflows, sets agent context per feature, builds, tests and ships from one interface.

Working memory for Claude Code - persistent context and multi-instance coordination

Context engine for large codebases, exposed through MCP. Gives AI coding agents precise repository context; benchmarked at frontier-agent quality with ~25x lower model cost and 45% fewer tokens with semantic search.

A proposed convention for the .agents/ directory to prevent context bloat and improve agent reasoning in complex codebases.

Cut AI context cost without trusting the compressor. Every reduction is reversible, byte-exact recoverable, and carries an auditable receipt. Local-first, works through proxy, MCP, SDK, or agent wrapper.

MCP server for persistent context management in AI coding assistants

BitDive Model Context Protocol (MCP) server. The Autonomous Quality Loop for AI agents. Provides real runtime context, before/after trace comparison, and integration testing workflows.

A practical, no-hype workflow for AI coding agents: context, plan, implement, review, QA, ship, retro. Templates, two Claude Code skills, and a 40% context rule - every claim traced to official docs.

A Model Context Protocol (MCP) server that retrieves information from Wikipedia to provide context to LLMs.

Stop re-explaining your data to your AI every session. The individual-analyst context layer, delivered over MCP (Claude Code / Cursor / Codex).

ktx is an executable context layer for data and analytics agents 🐙 Allow Claude Code, Codex, or other AI agents to query analytical databases accurately and with full context of your company

Keep Claude Code context clean. Open-source toolkit: drift detection, re-read dedup, integrity scoring, AST-aware reads, 15 MCP tools. 62.6% measured savings, reproducible.

Recursive Language Model patterns for Claude Code — handle massive contexts (10M+ tokens) by treating them as external variables

Compounding Context for AI Coding Assistants — MCP graph engine for Claude Code, Cursor, Copilot, Gemini, OpenCode

The Biomimetic Context Engine & Neural Runtime for AI Coding Assistants

The Context Layer for unstructured data: typed, versioned datasets over S3, GCS, Azure

Offline context handoff between coding agents. Read local histories into fresh sessions; source stores stay unchanged. Stdlib-only Python, not live session restore.

Let LLMs control embedded devices via the Model Context Protocol.