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

Enables cleaning and sanitizing prompts through an LLM-powered tool that removes sensitive information, provides structured feedback with notes and risks, and normalizes prompt formatting. Supports configurable local or remote OpenAI-compatible APIs with automatic secret redaction.

MCP server for managing and serving dynamic prompt templates using elegant and powerful text template engine. Create reusable, logic-driven prompts with variables, partials, and conditionals that can be served to any compatible MCP client like Claude Code, Claude Desktop, Gemini CLI, etc.

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.

Git-driven MCP server that manages and provides prompt templates with Handlebars support, enabling teams to collaborate on and version-control reusable, dynamic prompts across AI editors like Cursor and Claude Desktop.

Provides MCP clients a single decision-only tool to classify prompts as safe for local or cloud models, or as containing PII or jailbreak content, without executing actions or calling AI models.

Lets Claude read and write Prompt Studio projects as Flow text, with version history and a repo-synced .flow file.

MCP server for professional prompt engineering and agentic scaffolding, with cloud and local optimization.

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.

A Model Context Protocol server that converts Markdown documents to plain text with flexible options and dual protocol support.

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

Fix your vibe coding prompts before they reach the AI. Scores and rewrites across 4 dimensions — no API key, no server, just npx. Now with codebase-aware context injection for design, database, API, auth, testing, and state management.

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.

Converts any Python Click or Typer CLI into an MCP server automatically — zero-code transformation that introspects CLI commands and exposes them as MCP tools.

Enables existing Express routers to be exposed as MCP tools, dispatching tool calls through the Express middleware stack in-process without a network hop.

Auto-generates MCP tools from your OpenAPI spec, allowing natural language interaction with any API via configurable headers and serverless deployment.

MCP server that fetches remote or local HTML resources and converts them to Markdown, enabling AI clients to summarize or process web content.

Enhances and cleans raw prompts using AI to make them more clear, actionable, and effective. Provides quality assessment, suggestions, and supports both general and code-specific optimization modes.

A standalone proxy that transforms any OpenAPI or Swagger-described REST API into an MCP server by mapping API operations to executable MCP tools. It enables AI clients to interact with existing web services through automated HTTP requests based on their official documentation.

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

Automatically converts Swagger/OpenAPI specifications into dynamic MCP tools, enabling interaction with any REST API through natural language by loading specs from local files or URLs.