#74 · Primary category: AI Coding Assistants

context-mode

antigravity claude claude-code claude-code-hooks claude-code-plugins claude-code-skill codex codex-cli context-mode copilot cursor-plugin kiro mcp mcp-server mcp-tools openclaw opencode pi-agent skills zed-extension

Context window optimization for AI coding agents. Sandboxes tool output (98% reduction), persists session memory, and enforces routing across 17 platforms via MCP + hooks.

Project last updated:08/29/26

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Why we included this project

Anyone who has watched a long AI coding session lose the plot once the context window fills up will recognize the problem this project targets. Context Mode works at the Model Context Protocol layer. It sandboxes tool output, which the project says cuts what reaches the model by about 98 percent; session memory survives compactions, and requests route across seventeen coding platforms. It is a thin adapter that plugs into Claude Code, Codex CLI, VS Code Copilot, OpenCode, and similar tools, rather than a standalone assistant, so teams can standardize context handling without switching agents. An FTS5 knowledge base with intent-driven search lets agents retrieve prior work instead of re-reading everything, and the sandboxed execution tools push the model to compute results in code rather than dumping raw files into the window. For long coding sessions, that adds up to lower token spend and agents that stay coherent.

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