Context Engineering: Build Consistent, Accurate, Predictable AI Systems

[ICML 2026] Meta Context Engineering via Agentic Skill Evolution

Context-Engine MCP - Agentic Context Compression Suite

Save 94% on AI coding tokens. Index your codebase, agents search instead of reading files. Works with Claude Code, Codex, Copilot, Cursor, Gemini CLI. Local MCP server, free, open source.

A context engine that treats skills as software.

Ultimate Context Engineering Infrastructure, starting from MCPs and Integrations

The Biomimetic Context Engine & Neural Runtime for AI Coding Assistants

Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.

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.

Context engineering for AI agents. ~80% fewer tokens. Fix tool overload. Skills and memory with in-process BM25 and semantic retrieval. Progressive Disclosure. No vector DB.

A memory layer for AI Agents

Sovereign Digital Twins that execute operational processes inside secure, audited environments.

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

Tiger CLI is the command-line interface for Tiger Cloud. It includes an MCP server for helping coding agents write production-level Postgres code.

The theory of LLM wikis, running as one. A framework for agent-operated knowledge: typed, linked, review-gated markdown your agents execute.

Universal memory runtime for AI agents

Durable single-Agent Harness for TypeScript: recoverable Threads, context continuity, explicit side effects, and a native TUI.

Compiles AI agent traces and truns them into reusable context.

Awesome list for AI agent harness engineering: tools, patterns, evals, memory, MCP, permissions, observability, and orchestration.

Automatically create new skills based on past agent traces

LeanKG: Stop Burning Tokens. Start Coding Lean.

📚 Two books on harness engineering — the design philosophies behind Claude Code & Codex: constraints, query loops, context governance, multi-agent verification. harness-books.agentway.dev

The definitive resource for Agent Skills - modular capabilities revolutionizing AI agent architecture

Turn any technical book PDF into a Claude Code skill — ready to study, reference, and use while you work.