"Understanding Prompts or Prompt Engineering" matching MCP servers:

A minimal MCP server that exposes Gemini's web and multimodal understanding (video, audio, document, image) through five dedicated tools.

Enables searching for high-quality AI art prompts from Banana Prompts by tags or keyword queries, with direct links to full prompts and images.

Enables AI agents to maintain persistent, inspectable understanding through typed, revisable updates, and to coordinate multi-agent work via shared graph-based stigmergy.

Enables local video inspection and offline transcription with timestamped JSON and Markdown output, enforced filesystem boundaries, and reproducible content-addressed caching.

Enforces team engineering standards across Git, code review, Rails, frontend, deployment, incidents, observability, API design, database, ADRs, and technical debt, with tools for branch name and commit message validation.

A Model Context Protocol server for managing prompt templates as markdown files with YAML frontmatter, allowing users and LLMs to easily add, retrieve, and manage prompts.

Provides live wait times and office details for all 60 Oregon DMV field offices by scraping the ODOT website, with no authentication required.

A local STDIO MCP server that bridges MCP clients to the Codex CLI by sending instructions to a configured workspace, exposing task run, status, and result tools with a read-only sandbox and no remote transport.

MCP server that turns coding workflows into explicit execution graphs (DAG) with deterministic command execution, human-in-the-loop gates, and tamper-proof run history for Claude Code.

Enables creation, management, and templating of prompts through a simplified SOLID architecture, allowing users to organize prompts by category and fill in templates at runtime.

Enables repository-aware lifecycle management and controlled delegation of coding tasks to trusted worker harnesses via MCP, with execution isolation, recovery, and verified handoff.

Provides coding agents with a shared, Markdown-based engineering knowledge base to search, capture, create, and update internal conventions, API details, infrastructure configs, and development setup via lightweight MCP tools.

An enhanced MCP server that fetches prompts from GitHub repositories with intelligent discovery, composition, and management features.

Lets MCP hosts search the public Image3 GPT Image 2 prompt gallery, fetch complete prompts, list categories, and turn rough ideas into structured prompt briefs.

An MCP server that exposes three tools for auditing, scaffolding, and triaging agent intent specs against a unified template, helping prevent intent failures in AI agents.

An MCP server that gives an AI assistant a set of real mechanical-engineering tools. Provides deterministic tools like material properties, beam analysis, unit conversion, and curve fitting for engineering calculations.

Turns a prompt-engineering workflow into a workbench: it suggests candidate prompts with live sample replies, gives them LangGPT structure, rewrites them over multiple rounds, and proves the result against test cases with promptfoo-style assertions, model graders and DSPy-style train/dev search. Runs on any OpenAI-compatible provider using your own API key.

Enables searching the public C Dance AI prompt gallery, inspecting complete prompts, comparing production workflows, and turning rough ideas into structured video prompt briefs.

Enables deterministic, read-only design of OpenSora video prompts and shot plans, including prompt diagnosis and access to workflow guides, without generating videos or requiring API keys.

Local MCP server that uses a local Ollama model to rewrite rough prompt drafts into structured, optimized prompts for paid APIs, saving tokens and improving output quality.