MCP Prompt Library
Enables AI-assisted development by providing a library of 110+ curated prompts, workflows, and coding standards, with MCP tools for prompt retrieval, composition, and multi-step workflow chains.
README
<p align="center"> <h1 align="center">MCP Prompt Library</h1> <p align="center"> <strong>110+ curated prompts, workflows, and coding standards for AI-assisted development</strong> </p> </p>
<p align="center"> <a href="LICENSE"><img src="https://img.shields.io/badge/license-MIT-blue.svg" alt="License"></a> <a href="https://nodejs.org"><img src="https://img.shields.io/badge/node-%3E%3D18.0.0-brightgreen.svg" alt="Node.js"></a> <a href="https://modelcontextprotocol.io"><img src="https://img.shields.io/badge/MCP-compatible-purple.svg" alt="MCP Compatible"></a> <img src="https://img.shields.io/badge/tests-147%20passed-success.svg" alt="Tests"> </p>
<p align="center"> <a href="#quick-start">Quick Start</a> ⢠<a href="#features">Features</a> ⢠<a href="#mcp-server">MCP Server</a> ⢠<a href="#library-contents">Library</a> ⢠<a href="#integrations">Integrations</a> </p>
Why This Exists
AI assistants are powerful, but they're only as good as the prompts you give them. Most developers:
- Repeat the same prompts across projects
- Forget effective prompts they used before
- Struggle to compose complex multi-step workflows
- Lack consistency in AI-assisted development patterns
MCP Prompt Library solves this by providing:
| What | How |
|---|---|
| 110+ battle-tested prompts | Organized by development phase (planning, development, quality, operations, performance, maintenance, devex, security, evals) |
| MCP server with 15 tools | Direct integration with Claude, OpenCode, Cursor, and any MCP-compatible client |
| Smart suggestions | AI recommends prompts based on what you're doing |
| Workflow chains | Multi-step guided processes for features, bugs, refactoring, security |
| Composable snippets | Mix modifiers like ultrathink + security-first on any prompt |
Quick Start
š¦ Usage as npm Package (Best for Developers)
Install the library to use prompts programmatically in your own tools:
npm install @esreekarreddy/ai-prompts
import {
getPrompt,
searchPrompts,
composePrompts,
} from "@esreekarreddy/ai-prompts";
// 1. Get a specific prompt
const prd = getPrompt("prd-generator");
console.log(prd.content);
// 2. Search for prompts
const securityPrompts = searchPrompts("security");
// 3. Compose a custom prompt with modifiers
const complexTask = composePrompts([
"prd-generator",
"ultrathink",
"security-first",
]);
š„ļø Usage as MCP Server (Best for Cursor/Claude)
1. Clone & Build
git clone https://github.com/esreekarreddy/mcp-prompt-library.git
cd mcp-prompt-library/mcp-server
npm install && npm run build
2. Configure Your AI Tool
See Integrations for your specific tool (OpenCode, Claude Desktop, Cursor).
3. Start Using
Once connected, your AI assistant has access to all prompts:
"suggest prompts for what I'm doing"
"get the PRD generator prompt"
"start the new-feature chain"
"compose prd-generator with ultrathink"
Features
Smart Intent Detection
Tell your AI what you're doing, and it suggests the right prompts:
| You Say | It Suggests |
|---|---|
| "I need to build a new feature" | PRD generator, new-feature chain |
| "Stuck on a bug" | Deep debugger, debugging skill, bug-fix chain |
| "Security review before launch" | Security audit, security-hardening chain |
| "This code is a mess" | Code cleaner, refactoring skill, refactor chain |
| "Complex architecture decision" | Megathink modifier, senior-engineer persona |
Workflow Chains
Multi-step guided workflows for complex tasks:
| Chain | Steps | Use Case |
|---|---|---|
new-feature |
7 | From PRD to deployment |
bug-fix |
7 | Systematic debugging to resolution |
refactor |
6 | Safe refactoring with verification |
security-hardening |
7 | Comprehensive security review |
production-launch |
7 | Pre-launch checklist to deployment |
# Start a chain
node dist/cli.js chains # List available chains
start_chain chain="new-feature" # Via MCP tool
Composable Prompts
Combine any prompts with modifiers:
# CLI
node dist/cli.js compose prd-generator ultrathink security-first
# MCP Tool
compose_prompt items=["prd-generator", "ultrathink", "security-first"]
Quick Modifiers
Instant prompt enhancers:
| Modifier | Effect |
|---|---|
ultrathink |
Deep analysis with extended reasoning |
megathink |
Maximum thinking for architecture decisions |
critique |
Harsh, unfiltered feedback mode |
debug |
Systematic debugging approach |
plan |
Planning mode - no code yet |
secure |
Security-focused review |
simplify |
Explain like I'm 12 |
MCP Server
The MCP (Model Context Protocol) server exposes 15 tools to your AI assistant:
Library Tools
| Tool | Purpose |
|---|---|
get_prompt |
Fetch any prompt by name (fuzzy matching works) |
search_prompts |
Search library by keywords |
suggest_prompts |
Smart suggestions based on your intent |
enhance_prompt |
Analyze request and suggest approach + relevant prompts |
save_to_library |
Save new prompts to the library |
library_stats |
Library statistics |
random_prompt |
Random prompt for inspiration |
Chain Tools
| Tool | Purpose |
|---|---|
list_chains |
View available workflow chains |
start_chain |
Begin a multi-step workflow |
chain_next |
Advance to next step |
chain_status |
View workflow progress |
chain_step |
Jump to specific step |
Utility Tools
| Tool | Purpose |
|---|---|
compose_prompt |
Combine multiple prompts |
quick_prompt |
Instant one-liner modifiers |
detect_context |
Analyze project ā suggest stack-specific prompts |
How It Works
You: "Build a user authentication system"
ā
AI calls: suggest_prompts("Build a user authentication system")
ā
Returns: security-audit, new-feature chain, auth patterns
ā
AI calls: start_chain("new-feature")
ā
AI guides you through: PRD ā Architecture ā Implementation ā Testing ā Deploy
Library Contents
110+ curated resources across 8 categories:
mcp-prompt-library/
āāā prompts/ (38) - Copy-paste ready prompts
ā āāā planning/ PRD generator, scope killer, architecture
ā āāā development/ Debugger, code cleaner, tech debt
ā āāā quality/ Security audit, PR reviewer, changelog generator
ā āāā operations/ Observability, runbooks, incident helper, postmortem
ā āāā performance/ Profiler, load test planner, optimization guide
ā āāā maintenance/ Dependency upgrader, migration planner, tech spec
ā āāā devex/ Repo onboarding, CI fixer, codebase explainer
ā āāā security/ Prompt injection audit
ā āāā evals/ Response grader, consistency checker, quality rubric
ā āāā design/ Design system extractor
ā āāā analysis/ Deep debugger
ā āāā agentic/ Context manager, agentic loop, test-driven fix
ā āāā system/ Master system prompt for AI setup
āāā skills/ (8) - AI behavior definitions
ā āāā code-review, debugging, testing, refactoring, documentation...
āāā instructions/ (18) - Reusable system prompts
ā āāā personas/ Senior engineer, security expert, DevOps, UX
ā āāā standards/ TypeScript, React, Python, Go, Rust, FastAPI, Next.js
ā āāā workflows/ TDD, PR review, incident response, feature development
āāā templates/ (16) - Project scaffolding
ā āāā claude-md/ CLAUDE.md for Next.js, Python, Node.js, CLI tools
ā āāā cursor-rules/ .cursorrules for various stacks
ā āāā copilot/ GitHub Copilot instructions
ā āāā docs/ PRD, ADR, API spec, runbook templates
āāā chains/ (5) - Multi-step workflows
ā āāā new-feature, bug-fix, refactor, security-hardening, production-launch
āāā snippets/ (21) - Composable modifiers
ā āāā modifiers/ ultrathink, megathink, step-by-step, meta-cot
ā āāā output-formats/ JSON, markdown table, checklist, numbered list
ā āāā constraints/ Security first, MVP only, read-only, no external deps
ā āāā safety/ Fact-check, citation-required, uncertainty, injection-guard
āāā contexts/ (9) - Reference documentation
ā āāā stacks/ Next.js 14, FastAPI, Prisma
ā āāā patterns/ MCP server patterns, agentic coding
ā āāā guides/ API design, error handling
āāā examples/ (3) - Gold-standard samples
āāā PRDs, architecture docs, code reviews
Integrations
OpenCode
Add to ~/.opencode/config.json:
{
"mcp": {
"ai-library": {
"type": "local",
"command": [
"node",
"/path/to/mcp-prompt-library/mcp-server/dist/index.js"
],
"enabled": true
}
}
}
Claude Desktop
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"ai-library": {
"command": "node",
"args": ["/path/to/mcp-prompt-library/mcp-server/dist/index.js"]
}
}
}
Cursor
Add to .cursor/mcp.json in your project:
{
"mcpServers": {
"ai-library": {
"command": "node",
"args": ["/path/to/mcp-prompt-library/mcp-server/dist/index.js"]
}
}
}
VS Code + GitHub Copilot
Copy the prompt files to your workspace:
cp -r .github/prompts /path/to/your-project/.github/prompts
CLI Usage
Use the library directly from your terminal:
cd mcp-server
# Get a specific prompt
node dist/cli.js get prd-generator
# Search prompts
node dist/cli.js search "security"
# Get AI-powered suggestions
node dist/cli.js suggest "I need to refactor this messy code"
# Combine prompts
node dist/cli.js compose prd-generator ultrathink step-by-step
# View workflow chains
node dist/cli.js chains
# Library statistics
node dist/cli.js stats
# Random prompt for inspiration
node dist/cli.js random
Development
cd mcp-server
npm install # Install dependencies
npm run build # Build TypeScript
npm run test # Run tests (114 tests)
npm run dev # Watch mode
npm run typecheck # Type checking only
Architecture
- TypeScript - Full type safety
- Vitest - 114 tests with fast execution
- Zod - Runtime validation for configs
- chokidar - Hot-reload when library files change
- MCP SDK - Model Context Protocol integration
Contributing
See CONTRIBUTING.md for guidelines.
Ideas for contributions:
- Add prompts that worked well for you
- Add workflow chains for common tasks
- Add coding standards for new languages/frameworks
- Improve existing prompts with better examples
License
MIT - see LICENSE
Acknowledgments
Built with the Model Context Protocol by Anthropic.
<p align="center"> <strong>Your AI is only as good as your prompts. Keep them polished.</strong> </p>
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.