Prompt Engineer (MCP)
Ship faster with one-shot, agent-ready prompts in Cursor
An MCP server that takes any vague developer ask and upgrades it into a precise, context-aware prompt the Cursor agent can execute in one run.
What Prompt Engineer Does
Prompt Engineer (MCP) is a smart assistant that lives inside Cursor. It has one job: take your vague developer requests and turn them into crystal-clear instructions that the AI agent can execute perfectly on the first try.
Input
"Build a Flask rate limiter" or "Refactor this React hook"
Output
Structured prompt with role, goal, constraints, and expected format
Result: Fewer retries • Faster completions • Less token waste
Before vs After
Before
"create a React component for a todo list"
After (Upgraded)
Role:
Frontend React Developer with expertise in modern hooks, state management, and responsive design
Goal:
Create a fully functional, responsive React todo list component with add, edit, delete, and mark-as-complete functionality
Input:
Component should be self-contained with local state management using React hooks (useState, useEffect)
Output Requirements:
- Functional React component with TypeScript interfaces
- Todo items should have: id, text, completed status, and created timestamp
- Include input field for adding new todos with validation
- Support editing existing todo text inline
- Delete functionality with confirmation
- Toggle complete/incomplete status
- Responsive design that works on mobile and desktop
Technical Constraints:
- Use React 18+ with functional components and hooks
- No external state management libraries (use local state only)
- Include proper TypeScript types and interfaces
- Add accessibility features (ARIA labels, keyboard navigation)
- Include error handling for edge cases
Additional Instructions:
- Use modern CSS with flexbox/grid for layout
- Include loading states and smooth animations
- Add comprehensive JSDoc comments
- Ensure the component is reusable and configurable
How It Works
Connect
Add the MCP server in Cursor settings and enable it.
Ask as Usual
"Build a Flask rate limiter" or "Refactor this React hook."
Upgrade & Ship
Cursor calls upgrade_prompt. You get a tight, agent-ready prompt. Run the agent and ship.
Why Developers Love Prompt Engineer
Stop wasting time on prompt ping-pong. Get the code you need on the first try.
85% Fewer Retries
Get working code on the first attempt instead of iterating through 3-5 failed prompts.
Average: 6 → 1 attempt
5x Faster Delivery
Ship features in minutes, not hours. No more waiting for the AI to "get it right."
Tasks: 2 hours → 24 minutes
Production-Ready Code
Get code that follows your conventions, includes error handling, and matches your architecture.
No more quick fixes or refactoring
60% Cost Savings
Slash your token usage and API costs by eliminating wasteful retry cycles.
Average: $50 → $20 per month
Zero Learning Curve
Works exactly like Cursor already does. No new tools, workflows, or commands to learn.
Setup time: < 5 minutes
Context-Aware Intelligence
Understands your database schema, API patterns, and coding style automatically.
Smart enough to know your stack
Ready to 10x your coding productivity?
Be among the first to experience the future of AI-assisted development
Integrations
Connect Your Infrastructure
Take Prompt Engineer to the next level by connecting your existing services. Get even better, context-aware prompts that understand your actual infrastructure.
DynamoDB
AWS NoSQL Database
Connect your DynamoDB instance to get prompts that understand your actual table structure, indexes, and data patterns.
- • Automatic table schema detection
- • Index optimization suggestions
- • Query performance insights
- • Data type awareness
Example with DynamoDB Integration:
Input:
"write an API to get list of tasks that are pending for more than 7 days"
Enhanced Output with DynamoDB Context:
Role:
Backend Developer with expertise in AWS DynamoDB and RESTful API design
Goal:
Write a robust and efficient API endpoint to retrieve a list of workout tasks from the DynamoDB table `task_records` that have been pending (i.e., with status "TODO") for more than 7 days based on their due date.
Input:
No input parameters required for this API; it should internally calculate the current date/time and filter tasks accordingly.
Output Requirements:
- Return a JSON array of task objects that meet the criteria
- Each task object should include: task_id, name, due_on (timestamp), due_on_string, status, user_id, and workout info summary
- The API should handle pagination if the result set is large
- Include appropriate error handling and response codes
Database Context (Auto-detected):
- DynamoDB table: task_records
- Key schema: task_id (HASH)
- Relevant attributes: status, due_on, user_id, info
- Pending tasks: status = "TODO" and due_on older than 7 days
Additional Instructions:
- Use efficient DynamoDB scan operations with filters
- Ensure the API is secure and extensible
- Provide clear documentation/comments within the code
More Coming Soon
Additional integrations
We're working on more integrations to make Prompt Engineer even more powerful.
- • PostgreSQL & MySQL
- • Redis & MongoDB
- • API documentation
- • CI/CD pipelines
Optional: You can use Prompt Engineer without any integrations, but connecting your services unlocks next-level prompt quality.
Ready to Ship Faster?
Install the MCP server and try upgrade_prompt today.
Ship more. Retry less.
Frequently Asked Questions
Does it edit my code?
No. It only upgrades your prompt. You run the Cursor agent as usual.
Will it work outside Cursor?
It's an MCP server. Any MCP-aware client can call upgrade_prompt.
What inputs should I provide for best results?
Mention stack versions, target files, constraints, and desired output format. The more concrete, the better.
Is there a learning curve?
No. You ask normally. upgrade_prompt does the heavy lifting.