promptz.dev
Access and manage prompts from promptz.dev for developers.
promptz.dev MCP Server
Access prompts from promptz.dev directly within Amazon Q Developer.
This MCP server allows to access prompts from the promptz.dev API without copy-pasting, reducing context switching and friction in your development workflow.
Features
The promptz.dev MCP Server provides two main capabilities:
- Prompts - Executable functions to search and execute prompts.
- Rules - Executable functions to search for project rules and by integrating with other tools adding/updating them in your workspace.
Example Usage
Once the server is connected to Amazon Q Developer, you can use it with natural language like:
- "Search for CLI prompts about JavaScript"
- "Show me the prompt called 'React Component Documentation'"
- "Use the React Component Documentation prompt to improve my documentation"
- "Find project rules for CDK Development"
- "Add the CDK Project Structure project rule to my workspace"
Installation
Step 1: Get API Credentials
- Navigate to https://promptz.dev/mcp
- Copy the MCP settings like API Key, API URL or the sample MCP configuration snippet.
Step 2: Install the MCP Server
Open the Amazon Q Developer MCP client settings file located at ~/.aws/amazonq/mcp.json
Option 1: Using npx (Recommended)
The easiest way to use the server is with npx, which doesn't require installation:
- Add the following configuration to your Amazon Q Developer MCP client's settings file:
{
"mcpServers": {
"promptz.dev": {
"command": "npx",
"args": ["-y", "@promptz/mcp"],
"env": {
"PROMPTZ_API_URL": "your-api-url-from-promptz.dev",
"PROMPTZ_API_KEY": "your-api-key-from-promptz.dev"
},
"disabled": false,
"autoApprove": []
}
}
}
Option 2: Local Installation
- Clone the repository:
git clone https://github.com/cremich/promptz-mcp.git
cd promptz-mcp
- Install dependencies and build:
npm install
npm run build
- Add the following configuration to your MCP client's settings file:
{
"mcpServers": {
"promptz.dev": {
"command": "node",
"args": ["/path/to/promptz-mcp/build/index.js"],
"env": {
"PROMPTZ_API_URL": "your-api-url-from-promptz.dev",
"PROMPTZ_API_KEY": "your-api-key-from-promptz.dev"
},
"disabled": false,
"autoApprove": []
}
}
}
Troubleshooting
If you encounter issues with the server:
- Check that your API credentials are correct
- Ensure the server is properly configured in your MCP client
- Look for error messages in the logs located ad
~/.promptz/logs/mcp-server.log - Use the MCP Inspector for debugging:
# Run with environment variables
PROMPTZ_API_URL="your-api-url" PROMPTZ_API_KEY="your-api-key" npm run inspector
The Inspector will provide a URL to access debugging tools in your browser.
Development
For those who want to contribute or modify the server:
# Install dependencies
npm install
# Build the server
npm run build
# For development with auto-rebuild
npm run watch
# Run tests
npm test
Security Considerations
- This server only provides read access to prompts and does not implement any write operations
- API credentials are stored in your MCP client's configuration file
- All communication with the promptz.dev API is done via HTTPS
- The server logs to a file in your home directory (~/.promptz/logs/mcp-server.log)
Servidores relacionados
Scout Monitoring MCP
patrocinadorPut performance and error data directly in the hands of your AI assistant.
Alpha Vantage MCP Server
patrocinadorAccess financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
VibeCoding System
A conversation-driven development framework for rapid MVP and POC creation.
Context 7
Up-to-date Docs For Any Cursor Prompt
Apache SkyWalking MCP
An MCP server for integrating AI agents with the SkyWalking observability platform and its ecosystem.
Tox Testing
Executes tox commands to run Python tests with pytest. Requires the TOX_APP_DIR environment variable to be set.
QA Sphere
Integration with QA Sphere test management system, enabling LLMs to discover, summarize, and interact with test cases directly from AI-powered IDEs
Wopee MCP
AI testing agents for web apps — dispatch test runs, analysis crawls, and AI agent tests, fetch artifacts and project status
DeepRank
Optimize any site for AI search: get DeepRank methodology, optimization steps, and suggestions (llms.txt, JSON-LD, audit checklist) so your AI assistant can implement AI visibility in the repo.
AI Agent Timeline MCP Server
A timeline tool for AI agents to post their thoughts and progress while working.
VeyraX
Single tool to control all 100+ API integrations, and UI components
Reactive AI Agent Framework
A reactive AI agent framework for creating agents that use tools to perform tasks, with support for multiple LLM providers and MCP servers.