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title: How to build mobile apps with AI: the three tools that...
description: Building mobile apps with AI effectively comes down to three tools: skills, MCP servers, and context management. Skills are SKILL.md instruction files that AI...
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# How to build mobile apps with AI: the three tools that actually matter

**[Expo Blog](https://daily.dev/sources/expo-blog)** · 15 min read · 2 upvotes · 0 comments

## Summary

Building mobile apps with AI effectively comes down to three tools: skills, MCP servers, and context management. Skills are SKILL.md instruction files that AI coding agents (Claude Code, Cursor, Codex) read on demand using progressive disclosure, keeping context costs low. The Expo MCP server connects agents to external services like build dashboards, logs, and simulators, but loads all tool definitions upfront so should be used sparingly. Context discipline means keeping conversations under ~50% of the context window and branching threads by task. The post walks through a habit tracker example, showing how to apply liquid glass tab styling with a skill, fix a failing build via MCP, and manage ideation vs. implementation in separate conversation threads.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://expo.dev/blog/how-to-build-mobile-apps-with-ai-the-three-tools-that-actually-matter>

## Questions this post answers

### Is the Expo MCP server free to use now?

Yes, the Expo MCP server is free for everyone with an Expo account, whereas it used to be reserved for the paid plan. It exposes EAS builds, workflows, logs, and crash reports to an AI agent, letting it read data and take actions like investigating a failing build.

_Track pricing and access changes to developer tools like the expo mcp server on daily.dev._

### What is the difference between an AI skill and an MCP server for coding agents?

A skill is a lightweight SKILL.md instruction file an AI agent reads only when a task needs it, keeping context cost low through progressive disclosure. An MCP server connects the agent to an external service, like a build dashboard or database, but loads all its tool definitions into context upfront whether used or not, making it more expensive. Use skills for encoding how to build something, and MCP for reaching data outside the codebase.

_Compare tooling trade-offs like skills versus mcp servers before wiring up an AI coding workflow, on daily.dev._

### How much of an AI coding agent's context window should I use before responses get worse?

Stay under roughly 50% of the context window. Past that threshold, models tend to hallucinate more and each response costs more tokens. A fresh session typically starts around 5% from the system prompt, config, and skill descriptions, and a full ideation session can reach 30%, so keeping conversations focused and branching by task helps avoid crossing the limit.

_Developers tuning AI coding workflows can keep tabs on context-management practices like this via daily.dev._

## Similar posts on daily.dev

- [MCP servers vs. skills: Choosing the right context for your AI](https://daily.dev/posts/mcp-servers-vs-skills-choosing-the-right-context-for-your-ai-zvdsezrz1) · Red Hat Developer · 1 upvotes · 0 comments
- [MCP & Skills for AI agents](https://daily.dev/posts/mcp-skills-for-ai-agents-oqh2e5dc6) · Daily Dose of Data Science \| Avi Chawla \| Substack · 2 upvotes · 0 comments
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---

Tags: [#ai-agents](https://daily.dev/tags/ai-agents), [#mobile](https://daily.dev/tags/mobile), [#react-native](https://daily.dev/tags/react-native), [#mcp](https://daily.dev/tags/mcp)

[View this post on daily.dev](https://daily.dev/posts/how-to-build-mobile-apps-with-ai-the-three-tools-that-actually-matter-ykhhvvhrt)

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