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Prompyai

Scores prompts against a project’s codebase and returns context-aware suggestions, rewrites, and project summaries through MCP.

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Install Prompyai

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "prompyai": {
      "command": "npx",
      "args": [
        "-y",
        "prompyai-mcp"
      ],
      "env": {
        "ANTHROPIC_API_KEY": "YOUR_VALUE_HERE",
        "PROMPYAI_TELEMETRY": "YOUR_VALUE_HERE"
      }
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Values are written into the snippet above so you can paste it as is. They never leave your browser.

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Overview

The prompyai MCP server evaluates prompts against a real project using file paths, symbols, project structure, and optional session history. It returns a score across specificity, context completeness, task clarity, and file or folder anchoring, along with project-specific suggestions and an AI-enhanced rewrite. Use it with Claude CLI when you want prompts grounded in the codebase rather than evaluated as standalone text. It also exposes project context and a toggle for pausing automatic evaluation.

Use cases

  • Evaluate prompts against a monorepo before sending coding tasks
  • Identify missing file paths, symbols, context, and acceptance criteria
  • Generate project-grounded rewrites for Claude CLI prompts
  • Inspect a project summary of its stack, folders, and instruction files
  • Pause automatic prompt evaluation during a session

Key features

  • Automatic prompt scoring from 0 to 100
  • Four-dimension score breakdown with letter grades
  • Project-aware suggestions and AI-enhanced rewrites
  • File tree, technology stack, Git state, and symbol indexing
  • Claude Code session-history context
  • Evaluation toggle

Tools3

What Prompyai lets your agent do. Expand a tool for its parameters.

Self-reported~62 tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked 3d ago

Recent health check succeeded.

7/7 checks healthy over the last 41d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 11d ago via OSV.dev · prompyai-mcp (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars1Stargazers on the source repository.
npm downloads141Package downloads in the last 30 days.
Last commit7mo agoMost recent push to the default branch.
Tools exposed3Callable tools this server registers over MCP.

How Prompyai works

What the prompyai MCP server does

The prompyai MCP server reviews prompts in relation to the project they target. Each evaluation produces a score from 0 to 100, divided across four dimensions: specificity, context completeness, task clarity, and file and folder anchoring. The result includes improvement suggestions and may provide a rewritten prompt using project details such as file paths, verified symbols, and architecture.

The scoring model considers concrete actions, expected output formats, constraints, file references, error details, success criteria, @ mentions, and references to project entities. Scores are assigned letter grades from A through F. The server can also summarize the project’s technology stack, recent files, important folders, and AI instruction files.

How it works

The server indexes the workspace before evaluating a prompt. Its context pipeline examines the file tree, technology stack, Git state, and TypeScript symbols, then resolves references in the prompt against that information. It can read Claude Code conversation history when a session ID is supplied, which gives evaluations additional multi-turn context. Workspace packages are considered for monorepo technology-stack detection.

AI enhancement has two supported paths. With ANTHROPIC_API_KEY configured, the server sends the rewrite request to Claude Haiku directly. Without that key, it returns codebase context for Claude to use within the existing session. Both paths are described as using actual project paths and verified function or class names in the enhanced result.

Setup and configuration

Install the prompyai MCP server for Claude CLI with:

Terminal
claude mcp add prompyai -- npx prompyai-mcp serve

The documented quick start requires Node.js 20 or newer and Claude CLI. ANTHROPIC_API_KEY is optional; setting it enables direct Claude Haiku suggestions. Set PROMPYAI_TELEMETRY=false to opt out of anonymous telemetry.

Tools and capabilities

The prompyai MCP server exposes three tools:

  • evaluate_prompt is automatically called for each user message. It requires the prompt text and an absolute workspace_path; active_file and session_id are optional.
  • get_context returns the project summary and requires an absolute workspace_path.
  • prompyai_toggle enables or disables automatic evaluation through a required Boolean enabled value.

Automatic scoring can also be paused or resumed with phrases such as “pause prompyai” and “enable prompyai,” according to the documented feature list.

Limitations and notes

Direct AI rewrites require an Anthropic API key; without one, the server relies on Claude using the returned project context in the existing session. Evaluation quality depends on the workspace path and the project information available to the indexer. The project is licensed under MIT.

Read the full README View source on GitHub

Reviews

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Frequently Asked Questions about Prompyai

prompyai is an MCP server that connects Claude CLI to your project codebase for context-aware prompt evaluation. Its main tools score prompts, return project context, and toggle automatic evaluation. It can use file paths, verified symbols, workspace structure, and optional session history to produce suggestions and enhanced prompts.

Run `claude mcp add prompyai -- npx prompyai-mcp serve` in Claude CLI. The documented setup requires Node.js 20 or newer and Claude CLI, and does not require a sign-up or configuration file for basic use.

No, an Anthropic API key is optional. Setting `ANTHROPIC_API_KEY` lets PrompyAI request direct rewrites from Claude Haiku; without it, the server returns codebase context for Claude to use through the existing session.

Use the `prompyai_toggle` tool with `enabled` set to `false`, or say “pause prompyai” in the documented workflow. Set `enabled` to `true`, or say “enable prompyai,” to resume automatic evaluation.

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