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AI Apps That Work: free MCP server for people building AI apps

Your coding agent can look up what your AI features really cost and what to change: real cost per AI result, current LLM prices, model switch costs, model shutdown dates, A/B test sample sizes and LLM-judge checks.

This repository holds the setup docs and client config files. The server itself runs at aiappsthatwork.com; its code is not in this repository.

Connect

Claude Code

claude mcp add --transport http ai-apps-that-work https://aiappsthatwork.com/mcp

Add --scope user to have it in every project. Or copy .mcp.json into your project.

Cursor: add this to ~/.cursor/mcp.json (every project) or .cursor/mcp.json (one project). The same file is in .cursor/mcp.json.

{
  "mcpServers": {
    "ai-apps-that-work": { "url": "https://aiappsthatwork.com/mcp" }
  }
}

VS Code: copy .vscode/mcp.json into your project.

Claude on the web and desktop: add a custom connector with the URL https://aiappsthatwork.com/mcp and leave the advanced settings empty.

ChatGPT: in developer mode, create an app with the URL https://aiappsthatwork.com/mcp and no authentication.

Any other MCP client: use the URL above with the Streamable HTTP transport and no authentication.

Related MCP server: Modelmeter

Tools

Every tool is read-only and has a title.

Tool

What it returns

real_cost_per_result

Cost per request, real cost per result that worked, monthly wasted spend, credit pricing

model_switch_cost

List prices of both models, cost per 1,000 requests on six common tasks, the break-even point, the current model's shutdown date

model_prices

List prices, context size, price source, and the dates each price was checked and last changed

model_shutdowns

Announced API shutdowns, with the replacement and source

ab_test_sample_size

Results needed per version, and days at a given volume

judge_agreement

Agreement rate, Cohen's kappa, per-verdict precision and recall, and whether to trust the judge

build_judge_prompt

A pass/fail judge prompt for one kind of AI step

launch_checklist

The AI-specific checks still to do before launch, plus a request you can hand to a coding agent

Every answer includes a link to a page on aiappsthatwork.com that shows the same result.

Example prompts

  1. "What does Claude Fable 5.2 cost per million tokens, and when was that price last checked?"

  2. "We send about 40,000 support answers a month on GPT-4o at about 3,000 tokens in and 300 out, and 70% work first time. What does each answer that works really cost us?"

  3. "Is it cheaper to move our invoice extraction from GPT-4o to Gemini 3.8 Flash, and how often would Flash need to work first time to stay cheaper?"

  4. "Which OpenAI and Anthropic models are being shut down in the next three months, and what replaces them?"

  5. "Our prompt works first time 60% of the time and we hope a new version reaches 68%. How many results do we need per version at 200 a day?"

  6. "Here are 40 verdicts from our LLM judge next to a person's verdicts. Can we trust the judge?"

Data and limits

  • Prices for text models are re-checked daily against OpenRouter and LiteLLM. Each price carries the date it was checked and the date it last changed.

  • Inputs are computed in memory and thrown away. Nothing you send is stored.

  • For each call the server records the kind of agent, the client's name and version as it reports them, the tool name, success or failure, and duration. Never your address, your inputs or the answer, and no id that links your calls. See https://aiappsthatwork.com/privacy.

  • Each address can make 120 calls a minute.

Other ways in

Contact

Questions, bugs or a tool you'd like: open an issue here or write to amit@aiappsthatwork.com.

License

The docs and config files in this repository are MIT licensed. The hosted server is free to use.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

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