Lists prompt templates for engineering reasoning workflows, enabling structured thought through step-by-step reasoning, branching, merging, and validation.
Apache 2.0
136,029 tools. Last updated 2026-05-22 12:44
"An introduction to prompt engineering" matching MCP tools:
- Discover available prompt engineering techniques with acceptance statistics to enhance AI interactions through optimized method selection.MIT
- Improve prompt quality by applying optimal engineering techniques like chain-of-thought reasoning based on intent analysis.MIT
- Provide answers to clarifying questions to continue prompt engineering for Claude Code, enabling interactive refinement of optimized prompts.MIT
- Dispatch engineering tasks to an AI agent for automated implementation and problem-solving.MIT
- Approve or decline an introduction request, optionally specifying fields to disclose and a response message.Apache 2.0
Matching MCP Servers
- AlicenseAqualityCmaintenanceRoutes one brief to the right image model across 60+ (gpt-image-1.5, Ideogram 3, Recraft V4, Flux), validates the output, and fans out to iOS/Android/PWA/favicon/visionOS/Flutter bundles. Works without an API key via Pollinations, HF Inference, Stable Horde, or host-LLM inline SVG.Last updated2246
- Alicense-qualityBmaintenanceEnables AI coding environments to enforce engineering governance through MCP tools and resources for init, check, route, and review workflows.Last updated2MIT
Matching MCP Connectors
Cloudflare Workers MCP server: ai-prompt-optimizer
Transform any blog post or article URL into ready-to-post social media content for Twitter/X threads, LinkedIn posts, Instagram captions, Facebook posts, and email newsletters. Pay-per-event: $0.07 for all 5 platforms, $0.03 for single platform.
- Call before coding or reviewing code to receive an engineering scaffold that identifies failure patterns, provides correct-pattern examples, and verifies correctness.MIT
- Retrieve the capabilities exposed by an MCP server instance, including total counts and current tool, resource, and prompt surfaces. Use for server-specific exposure instead of integration-level lists.MIT
- Delete a prompt and all its versions by prompt ID. Irreversible action that breaks callers using the slug; confirm removal with list_prompt_versions first.MIT
- Create a label to tag prompt versions like production or staging. Specify organization or workspace scope to get a new label ID without assigning it to versions.MIT
- Score and optimize LLM prompts using multi-framework analysis. Returns improved prompt versions with detailed breakdowns across 8 quality dimensions including PEEM, RAGAS, G-Eval, and MT-Bench criteria.MIT
- Update an existing prompt with new fields, archive the old version, and publish to activate changes. Supports both single and multi-message formats.MIT
- Generate structured prompt templates from feature requirements or existing prompts to enable systematic testing and evaluation of AI applications.Apache 2.0
- Replace the background of an input image with a new scene described by a text prompt, using customizable visual styles.MIT
- Generate a logo from a brief. Choose inline SVG (no API key), external prompt (paste targets), or API (requires key). Returns an asset bundle or plan. Supports 60+ image models.
- Transform an input image into a new image guided by a text prompt, adjusting the influence of the original image with a strength parameter.MIT
- Create a new Engineering Change Notice (ECN) for a project. Specifies ECN details like type, severity, and disposition, then commits to a branch or opens a pull request.Apache 2.0
- Generate engineering change notice suggestions from failure analysis data to address paste aperture changes, AVL updates, or design modifications.Apache 2.0
- Retrieve a specific prompt template from LangSmith by providing its exact name, enabling prompt reuse and management in language model workflows.MIT
- Lists Engineering Change Notices (ECNs) in a project, with optional filters by severity, status, and type.Apache 2.0