MCP & the tool-use layer — what's accelerating
The tool-use layer is what turns a chatbot into an agent that can actually do things — CLIs, plugins, protocol bridges and context graphs. But this bucket is also crowded with "skill" packs that ride the MCP tag without shipping a tool. Genuine plumbing first, skills wave clearly cordoned off at the bottom.
Top mover
A plugin that lets you call Codex from inside Claude Code to review code or delegate tasks — a first-party bridge between two rival agent runtimes. The story here is interoperability: instead of picking one coding agent, you wire them together and let each do what it's best at. (Two faster repos sit above it on raw velocity; both are skill packs — see below.)
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MCP & tool-use plumbing
real substanceOne command-line tool for Drive, Gmail, Calendar, Sheets, Docs, Chat and Admin, dynamically built from Google's discovery API. It matters because it gives an agent a single, uniform surface onto all of Workspace rather than seven bespoke integrations — exactly the kind of consolidation the tool-use layer needs.
Hundreds of models and providers, one command to find what actually runs on your hardware. A small, sharp utility that solves the unglamorous "will this model even fit?" question before you waste a download.
A local-first code intelligence graph exposed over MCP and CLI, building a persistent map of your codebase so AI tools read only what matters. This is the MCP-native version of the code-graph idea: the agent queries the graph as a tool rather than re-scanning files.
An open-source long-horizon agent harness that researches, codes and creates using sandboxes, memory, tools and sub-agents. A full orchestration runtime from ByteDance — substantial enough that the tool-use machinery is the point, not a bolt-on.
An open-source "Agent Operating System" with MCP and LLM wiring built in. Early and ambitious, but it's genuine runtime work — a place agents and their tools run — not a prompt bundle.
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The skills wave
trend signal, not infrastructureThe two fastest repos in this entire bucket are skills, not tooling — which is the honest headline. alchaincyf/nuwa-skill (⭐22,947 · ↑370.1/day, "distill how anyone thinks") and Leonxlnx/taste-skill (⭐34,733 · ↑327.7/day, "gives your AI good taste, stops it generating generic slop") are outrunning every genuine CLI and runtime here. Add titanwings/colleague-skill (⭐19,074 · ↑280.5/day) and mvanhorn/last30days-skill (⭐28,440 · ↑213.8/day, multi-platform topic research) and the pattern is clear: people are packaging judgment and persona, not protocol. That's a real signal about what users want from agents — taste, voice, synthesis — but a skill that tags mcp is not the same as a tool that implements it, so they stay out of the plumbing list above.
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How this was made
Live GitHub pull, bucketed by MCP and tool-use keywords, verified not-archived and pushed recently, ranked by stars/day, then hand-separated into genuine tools/protocol work vs. skill-pack noise. Counts pulled at publish — re-verify before reposting.
Accelbrief · catch acceleration, not stars · all editions