mcp-apps-builder

mcp-apps-builder is a skill for Claude Code, Codex from Shubhamsaboo/awesome-llm-apps. It costs 139 tokens per session (3,017 once invoked), scanned A, original, Apache-2.0.

A required guide for building Model Context Protocol (MCP) servers with the mcp-use framework. MCP servers connect AI assistants to tools, data resources, prompts, and interactive widgets.

In plain words
What is it for?
Use it before creating, changing, debugging, or reviewing an mcp-use MCP server.
Why use it?
It helps choose the right implementation guidance and checks whether an existing mcp-use project should be extended instead of recreated.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it before creating, changing, debugging, or reviewing an mcp-use MCP server.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/shubhamsaboo/awesome-llm-apps/mcp-apps-builder
About the project

Awesome LLM Apps is a collection of open-source applications built around large language models, including AI agents and retrieval-augmented generation apps. It is intended for developers who want to study, run, or adapt these applications and related agent skills.

Shubhamsaboo/awesome-llm-apps · 137,243 stars · on GitHub · theunwindai.com

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Shubhamsaboo/awesome-llm-apps --skill mcp-apps-builder
Clone the repo
git clone --depth 1 https://github.com/Shubhamsaboo/awesome-llm-apps

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for mcp-apps-builder

README.md
[![agentmods](https://agentmods.dev/badge/skills/shubhamsaboo/awesome-llm-apps/mcp-apps-builder/github.svg)](https://agentmods.dev/skills/shubhamsaboo/awesome-llm-apps/mcp-apps-builder)
Your own site
<a href="https://agentmods.dev/skills/shubhamsaboo/awesome-llm-apps/mcp-apps-builder"><img src="https://agentmods.dev/badge/skills/shubhamsaboo/awesome-llm-apps/mcp-apps-builder/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for mcp-apps-builder

Your own site · 80×15
<a href="https://agentmods.dev/skills/shubhamsaboo/awesome-llm-apps/mcp-apps-builder"><img src="https://agentmods.dev/badge/skills/shubhamsaboo/awesome-llm-apps/mcp-apps-builder.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 139 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,017 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Snyk pass 7 Sept 2026
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 3 findings, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium MCP Rug Pull · line 45
    npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.
    Fix: Pin the version: npx @scope/[email protected]
  • medium MCP Rug Pull · line 60
    npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.
    Fix: Pin the version: npx @scope/[email protected]
  • medium Excessive Agency · line 222
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00139 $0.03017
Opus 5 $0.00069 $0.01509
Sonnet 5 $0.00028 $0.00603
Haiku 4.5 $0.00014 $0.00302

Measured 13d ago against content hash bc446a219507, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

mcp-apps-builder scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

4 near-identical copies found in the catalogue:

generative_ui_agents/ai-mcp-app-builder/apps/mcp-use-server/.agent/skills/mcp-apps-builder/SKILL.md · 356 lines

How it starts

The opening of the file, as written. The whole thing — 356 lines — stays where its author put it; the contents beside it link to each section on GitHub.

IMPORTANT: How to Use This Skill

This file provides a NAVIGATION GUIDE ONLY. Before implementing any MCP server features, you MUST:

  1. Read this overview to understand which reference files are relevant
  2. ALWAYS read the specific reference file(s) for the features you're implementing
  3. Apply the detailed patterns from those files to your implementation

Do NOT rely solely on the quick reference examples in this file - they are minimal examples only. The reference files contain critical best practices, security considerations, and advanced patterns.


MCP Server Best Practices

Comprehensive guide for building production-ready MCP servers with tools, resources, prompts, and widgets using mcp-use.

⚠️ FIRST: New Project or Existing Project?

Before doing anything else, determine whether you are inside an existing mcp-use project.

Detection: Check the workspace for a package.json that lists "mcp-use" as a dependency, OR any .ts file that imports from "mcp-use/server".

├─ mcp-use project FOUND → Do NOT scaffold. You are already in a project.
│  └─ Skip to "Quick Navigation" below to add features.
│
├─ NO mcp-use project (empty dir, unrelated project, or greenfield)
│  └─ Scaffold first with npx create-mcp-use-app, then add features.
│     See "Scaffolding a New Project" below.
│
└─ Inside an UNRELATED project (e.g. Next.js app) and user wants an MCP server
   └─ Ask the user where to create it, then scaffold in that directory.
      Do NOT scaffold inside an existing unrelated project root.

NEVER manually create MCPServer boilerplate, package.json, or project structure by hand. The CLI sets up TypeScript config, dev scripts, inspector integration, hot reload, and widget compilation that are difficult to replicate manually.


Scaffolding a New Project

npx create-mcp-use-app my-server
cd my-server
npm run dev

For full scaffolding details and CLI flags, see quickstart.md.

Read the full file on GitHub · 356 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 13d ago First seen · 356 lines · 139 tokens per session scan A bc446a219507

Subscribe to this mod's changes

mcp-apps-builder is a skill published in the GitHub repository Shubhamsaboo/awesome-llm-apps (137,243 stars, last pushed yesterday), licensed Apache-2.0. It adds 139 tokens to every session and 3,017 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

guardrails-developer-guide

Routes NVIDIA NeMo Guardrails library product-usage questions to the canonical documentation. Use when users ask how to install, configure, integrate, evaluate, observe, deploy, troubleshoot, or use the NVIDIA NeMo Guardrails library. Trigger keywords - install guardrails, configure rails, guardrail catalog, Colang…

NVIDIA-NeMo/Guardrails · 92 tokens

daily-ai-news-digest

Fetches articles from 92 Karpathy-curated RSS feeds, scores them with an LLM, selects the top 3, and delivers a formatted digest to Telegram every morning.

Sumanth077/Hands-On-AI-Engineering · 42 tokens

mem0-status

Diagnoses mem0 connectivity, API key validity, and memory read/write functionality. Use when memory operations fail, searches return empty, addmemory errors occur, or to verify the plugin is working correctly.

mem0ai/mem0 · 44 tokens

hugging-face-model-trainer

This skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV…

patchy631/ai-engineering-hub · 131 tokens

hugging-face-evaluation

Add and manage evaluation results in Hugging Face model cards. Supports extracting eval tables from README content, importing scores from Artificial Analysis API, and running custom model evaluations with vLLM/lighteval. Works with the model-index metadata format.

patchy631/ai-engineering-hub · 55 tokens

hugging-face-datasets

Create and manage datasets on Hugging Face Hub. Supports initializing repos, defining configs/system prompts, streaming row updates, and SQL-based dataset querying/transformation. Designed to work alongside HF MCP server for comprehensive dataset workflows.

patchy631/ai-engineering-hub · 49 tokens