"Information or resources related to 'Prompt'" matching MCP servers:

Enables an MCP-compatible AI client to author Blender Python, run Blender, import the resulting asset into Unity with materials and a prefab, place it in the active scene, verify the import, and revise the same asset using stable IDs.

MCP server that provides OpenRouter model pricing data, enabling price lookups, trending/cheapest lists, and model searches without an API key.

A Model Context Protocol server that enables Claude to execute Python code using boto3 to query and manage AWS resources directly from conversations.

MCP server that demonstrates the Resources feature by exposing static and dynamic resources, including contact data and personalized greetings, through MCP.

HandaaS的MCP服务器，提供全域资讯搜索、企业新闻、行业资讯、主题跟踪和企业动态监控能力，帮助用户开展行业研究和舆情分析。

Provides a local MCP interface to query captured, PII-scrubbed prompt telemetry from coding agents and browser chats, enabling time summaries, prompt search, and activity analysis without data leaving the machine.

Enables dynamic prompt management by automatically discovering and serving markdown prompt files with YAML frontmatter via the Model Context Protocol.

A lightweight MCP server that provides a unified interface to various LLM providers including OpenAI, Anthropic, Google Gemini, Groq, DeepSeek, and Ollama.

Enables users to manage, search, render, version, and regression-test local Markdown templates with typed variables, and to expose them as MCP tools and native prompts without requiring a model API, account, or cloud service.

Smart AI workflow for Cursor teams with intelligent prompt routing, real-time cost optimization, and team analytics.

This MCP server provides research-backed prompt optimization tools and professional domain templates designed to improve AI performance through strategies like Tree of Thoughts and Medprompt. It enables users to analyze, auto-optimize, and refine prompts using advanced reasoning patterns and safety-critical alignment techniques.

A deterministic prompt optimization middleware for AI coding agents that preserves intent, compresses context, and detects drift, available as an MCP server with tools for optimize_prompt, classify_prompt, and more.

MCP server exposing prompt-shield's prompt-injection firewall for LLM applications. Four tools — scan_input, scan_output, scan_tool_result (with optional sanitization), and list_detectors — backed by 34+ detectors and a federated ed25519-signed threat feed.

Retrieval-grounded prompt refinement engine that repairs and polishes prompts via a single LLM call, exposing a refine_prompt tool for integration with MCP-compatible hosts.

A standalone MCP server that enforces clean prompt structure, strips model‑invented instructions, and detects capability hallucinations before they propagate through your system.

Provides current weather information for any location and generates AI-powered responses using Google Gemini through FastMCP.

MCP server providing on-demand access to official prompting guides for building robust meta-prompts.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Transforms rough or follow-up prompts into self-contained, model-ready prompts by profiling the task and conversation, applying research-backed techniques, and returning citations, assumptions, and clarifying questions.

Community-driven library of tested prompts for AI agents, enabling search, retrieval, sharing, and rating of prompts.

Enables users to turn any API's documentation into a tested MCP server whose tools expose the API's own operations, with linting, contract tests, and live verification. It accepts OpenAPI/Swagger, Postman, RAML, WSDL, GraphQL, RSS, and HTML docs.

MCP server for community-driven prompt voting and discovery — submit, upvote, and find the best AI prompts.

Enables searching and retrieving documentation from crawled documentation sites as an MCP server, allowing coding agents to query real docs instead of relying on training data.

Stateful interactive HTTP REPL and Agentic MCP engine for API navigation and testing.

WAF for AI agents — block prompt injection before it reaches the LLM.

A server that transforms a standard Language Model into a dynamic multi-agent system where the model simulates both a Conductor (project manager) and Experts (specialized agents) to tackle complex problems through a collaborative workflow.

An MCP server that allows agents to test and compare LLM prompts across OpenAI and Anthropic models, supporting single tests, side-by-side comparisons, and multi-turn conversations.

Generates standalone, human-readable MCP servers from RAML 1.0 or OpenAPI 3.x specs, exposing one tool per resource and method that makes real HTTP calls. It understands Mule/Anypoint auth patterns such as Client ID enforcement and OAuth2, wiring the expected credentials from environment variables at call time.

Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.

A demonstration MCP server for exploring MCP prompts with 10 reusable development prompts.