#prompt-engineering

A standardized framework for enhancing how LLMs process and respond to prompts through composable decorators, featuring an official open standard specification and Python reference implementation with MCP server integration.

Global Notion workspace-accessible MCP server for all Notion pages within the workspace

A Python MCP server that wraps the Gelbooru API. Connect it to any MCP-compatible client (Claude Desktop, Cursor, etc.) to search posts, look up tags, and generate Stable Diffusion prompts from real character appearance data — all directly from your AI assistant.

An LLM-based smart terminal for lazy guys :P

This repo is dedicated to learning and working with large language models (LLMs), prompt engineering, and modern GenAI tools such as LangChain, RAG, and vector databases.

CTX: The missing link between your codebase and your LLM. Context as Code (CaC) tool with MCP server inside.

PromptStudio - An MCP server and Application for managing AI prompts with collections, variables, execution history, and import/export capabilities.

Automatable GenAI Scripting

A Model Context Protocol (MCP) Gateway. Serves as a central management point for tools, resources, and prompts that can be accessed by MCP-compatible LLM applications. Converts REST API endpoints to MCP, composes virtual MCP servers with added security and observability, and converts between protocols (stdio, SSE).

Model intelligence for AI agents — syntax, parameters, pricing, and routing for 67+ generative AI models (Midjourney, Flux, Suno, Runway, DALL-E, Stable Diffusion). 7 tools that let any MCP client recommend, compare, optimize, and price AI model calls.

PQS is the fastest way to get better output from any AI model. Score any prompt before it hits the model. Get a grade (A-F), score out of 80, percentile, and 8-dimension breakdown across clarity, specificity, context, constraints, output format, role definition, examples, and chain-of-thought structure. Built on PEEM, RAGAS, MT-Bench, G-Eval, and ROUGE frameworks. Pre-flight, not post-hoc. The AI input quality problem is real. PQS solves it. MCP Tools: - score_prompt: Free. Returns grade (A-F), score out of 80, percentile, and full 8-dimension breakdown. No API key needed. - optimize_prompt: $0.025 USDC via x402. Returns a rewritten, higher-scoring version of your prompt with before/after dimension deltas. Requires API key from promptqualityscore.com. HTTP API (x402-native on Base): - /api/score/free: Free. Grade, percentile, and 8-dimension breakdown. No payment required. - /api/score: $0.025 USDC. Single score, pay-per-call. - /api/score/full: $0.125 USDC. Grade, percentile, dimension breakdown, and rewrite. - /api/score/batch: $0.25 USDC. Score multiple prompts in a single call. - /api/preflight: $0.05 USDC. Lightweight pre-flight quality check. Paste a prompt. Get an optimized version. Ship better work. Cheaper than one bad prompt. https://promptqualityscore.com

130+ QA & dev tools for AI agents. Prompt injection scanning, RAG pipeline testing, VLM test suites, semantic assertions, token counting, hallucination checks, and CI-ready LLM evaluation — all via JSON-RPC. Free, no API key, no signup.