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Official & CollectionsComposioHQ/awesome-claude-skillsFeatured

A curated index of 1000+ skills, plus one genuinely unique connect-apps plugin

Editor's takeThere is no one-liner that installs this repo; use it as a discovery layer. A list answers what exists, not what is worth running. The part you cannot get elsewhere is connect-apps-plugin: a single MCP endpoint to 1000+ integrations with authentication, team-level ACLs and audit logs, which is exactly the governance problem enterprises hit when agents touch SaaS.

A list maintained by Composio at 75k stars with an Apache-2.0 badge in the README. About 31 first-party skill directories physically exist here while the index references 864 SKILL.md files, and most of the difference is links out to external repositories. Coverage explicitly extends beyond Claude.ai and Claude Code to Codex, Cursor, Gemini CLI and Antigravity.

Any agent
claude --plugin-dir ./connect-apps-plugin
PythonComposioHQ75.4k
A curated index of 1000+ skills, plus one genuinely unique connect-apps plugin
ahujasid/mcp-for-blenderMIT

MCP for Blender: 32 tools that make Blender a 3D workspace an LLM can drive

Formerly blender-mcp, a third-party community plugin (the README states on its first screen that it is not made by Blender), MIT licensed, Python, and the highest-starred entry among 3D MCP servers. The PyPI package is now mcp-for-blender, yet uvx blender-mcp still runs and existing configs need no change. Two components only: an addon inside the Blender process runs a socket server that actually executes commands (the only place with bpy, the current scene and the UI thread), while a separate MCP server process translates protocol, joined by JSON over TCP on localhost:9876 by default. The source defines 32 @mcp.tool() decorators across four layers - perception (get_scene_info, get_object_info, get_viewport_screenshot returning an MCP Image, closing an act-then-look loop), reference lookup (bpy_api_lookup and describe_node_type so the model queries instead of guessing socket order and enum names), execution (execute_blender_code as the escape hatch, set_texture, export_scene to GLB/FBX), and asset retrieval and generation (Poly Haven with semantic search, importing the .blend source and writing attribution properties; Poly Pizza with about 10,600 low-poly models, size normalisation and automatic CC-BY credit; Sketchfab; Hyper3D Rodin text-to-3D and image-to-3D; Tencent Hunyuan3D distinguishing the mainland ai3d endpoint from the international hunyuan one). On security, arbitrary code execution is the design rather than a bug: an optional safe mode (BLENDER_MCP_SAFE_MODE=1) statically validates scripts before running, blocking file access, subprocesses, network and persistent code while modelling, rendering, saving, import and export pass normally, and blocked scripts return to the model with the reason so it can retry. Content telemetry is off by default, and a dedicated disable_telemetry tool can only turn collection off. 29.2k stars. Not run with Blender locally yet, so this is graded as pending reproduction.

MCPBlender3D Generation
Python29k2.7k202
GLips/Figma-Context-MCPMIT

Framelink MCP for Figma: design files compressed into usable context, not screenshots

Also known as Figma-Context-MCP, npm package figma-developer-mcp, TypeScript, MIT, and a third-party implementation rather than the Dev Mode MCP server Figma ships itself. It exposes only two tools: get_figma_data (read-only) and download_figma_images (removable with –skip-image-downloads, and confined to writing inside –image-dir). The narrow surface is deliberate; the engineering sits in the fetch → simplify → serialize pipeline behind it. Simplify uses composable extractors (layout, text, visuals, component, plus the allExtractors, layoutAndText, contentOnly, visualsOnly and layoutOnly bundles) to compress the raw Figma response into semantic layout and styling in a single tree walk, with maxDepth and nodeFilter, and outputs tree (default, cheapest in tokens), yaml or json. The part worth copying is that compression effectiveness is a metric computed on every call: rawSizeKb against simplifiedSizeKb, rawNodeCount against simplifiedNodeCount, component/instance/text/image node counts, namedStyleCount (the source comment states a high count is a design-system maturity signal), hasVariables (whether Figma Variables are used at all), and separate fetch/simplify/serialize timings; the same hooks drive MCP progress notifications and heartbeats so a large file taking tens of seconds does not look hung. Judgement shows in the details: node IDs accept both the plain and the deeply nested instance shape, the depth parameter description says do not use it unless the user explicitly asks, the proxy default deliberately avoids installing EnvHttpProxyAgent when no proxy variables exist so a stale variable cannot route traffic through an intermediary returning 403, and stdio mode warns at startup when –image-dir is unset. Credentials come from FIGMA_API_KEY or FIGMA_OAUTH_TOKEN; telemetry can be disabled with –no-telemetry or DO_NOT_TRACK=1 and secrets are redacted from reports. 15.9k stars. It generates no frontend code - the output is design facts, and translating them into React, Vue or SwiftUI is your coding agent job. Not yet run against a Figma file of our own, and no screenshot-versus-structured-data accuracy comparison, so this is graded as pending reproduction.

MCPFigmaDesign-to-Code
TypeScript16k1.3k65
Speech & AudioMediaTopA

VoiceStudio: the commercial voice stack moved onto local hardware and opened to agents by default

An open source, fully local voice workstation (debpalash/VoiceStudio, AGPL-3.0, Python plus Electron) positioned as the local alternative to ElevenLabs: voice cloning, voice design, video dubbing, dictation, transcription and audiobook creation, with a claimed 646 languages. Created on 2026-04-09 and at 42,831 stars and 5,005 forks on 2026-09-29. It sits at the top self-hosted row in the audio domain, not because any model behind it is stronger, but because the abstraction layer is useful. Open voice capability is scattered across a dozen repositories with their own weight formats, device requirements, cloning interfaces and licences, so assembling a pipeline of clone a voice, transcribe, align, dub and produce an audiobook spends most of its effort on glue. VoiceStudio collects 17 TTS and 11 ASR engines into one registry and reports per engine which devices it runs on (CUDA, MPS, CPU), whether it can clone, and its max_ref_seconds and ref_strategy, on top of a workflow that actually runs. The agent surface matters most for the catalogue: a local API and an MCP server ship as first class product features, the README includes an installation prompt ready to paste into Claude Code, Codex or Cursor, and npx skills add installs it as a skill, which means coding agents can call dubbing and transcription as tools rather than needing a human at the interface. The reference audio policy is equally rigorous, with a 75 second ceiling while how much of a longer clip reaches the model depends on the engine and is reported per engine, an automatic or saved transcript ignored beyond the limit, and a hard [clone_ref_too_long] error when sending more than 20 seconds plus transcript text to the default OmniVoice. One measurement point needs stating plainly: the official docs/benchmarks.md contains a real harness with per stage profiling, refusal to start when memory is insufficient, and a rule that only RTF warm and peak memory on named hardware and versions are accepted with no estimated numbers allowed, but the results column reads No verified rows yet. therefore attach no performance figure at all and the card carries only the star count verified ourselves through the GitHub API, which is what earns the A grade. That A asserts the number is real and nothing about being better than ElevenLabs. Four boundaries: AGPL-3.0 is strong copyleft with a network clause, so embedding it in a service offered to outsiders obliges you to release your own server side source, and closed commercial use means either process isolation calling only the local API under your own legal review or assembling the pipeline from Apache-2.0 pieces such as CosyVoice 3 or Kokoro; per-model licences are not settled by the wrapper, since the Breeze-TTS-2 weights behind audio.cpp are research and non-commercial, Supertonic-3 and PocketTTS need extra permissions and GPT-SoVITS requires its own server, so check every model before commercial use; the 646 language figure is the repository own claim and real coverage depends on the engine chosen, from 25 European languages on Parakeet through 50 plus on FunASR to the wider Whisper family, unverified language by language; and desktop is Electron only now, with 0.5.3 the last Tauri release, so existing users must migrate. It sits alongside Eleven v4 on the ladder rather than replacing it, one representing the quality ceiling and convenience of a closed commercial stack and the other the data sovereignty and engine substitutability of local self-hosting.

42,831GitHub stars (2026-09-29, verified here via GitHub API)Confirmed · 2026-09
Productdebpalash (open source)SiteRepo
VoiceStudio: the commercial voice stack moved onto local hardware and opened to agents by default
AI CodingDevelopmentC

v0: the code-generation agent that opens its own app, uses it, and ships through your protected branch

Vercel's v0 has the most complete agent loop among closed full-stack generators: web search with clickable citations, a browser that actually uses the app it built and sends back screenshots, terminal and unit tests inside a sandbox, bring-your-own MCP for external tools, and since Sep 2026 a one-step Publish that walks PR to merge to deploy for GitHub projects. Its boundaries are equally clear: the default stack is Next.js + shadcn, the shortest path is locked to Vercel, credits scale with iteration rounds, and there is no public correctness benchmark.

One-step PR → merge → deployGitHub project release pathVendor Claim · 2026-09
ProductVercelSite
v0: the code-generation agent that opens its own app, uses it, and ships through your protected branch

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