Retrieve prompt templates for ADR generation and analysis on-demand, reducing token usage by loading only when needed.
MIT
114,411 tools. Last updated 2026-04-21 10:22
- Improve prompt quality by applying optimal engineering techniques like chain-of-thought reasoning based on intent analysis.MIT
- Access built-in AutoHotkey v2 prompt templates to generate code and learn scripting techniques through structured examples.
- Provide answers to clarifying questions to continue prompt engineering for Claude Code, enabling interactive refinement of optimized prompts.MIT
- Create marketing images using AI-powered templates for social media, banners, and web content. Choose prompt-based generation or direct template control with customizable branding, styles, and sizes.MIT
- Create reusable document templates with HTML/Handlebars markup and JSON schema for generating PDFs like invoices, contracts, and reports.MIT
Matching MCP Servers
- AsecurityFlicenseBqualityA Model Context Protocol server that allows creation and management of multiple Fireproof JSON databases with CRUD operations, querying capabilities, and cloud synchronization for sharing databases with others.Last updated96
- -securityAlicense-qualityEnables AI models to interactively prompt users for input or clarification directly through their code editor. It facilitates real-time communication between assistants and users during development tasks.Last updatedMIT
Matching MCP Connectors
Compare two JSON files deeply without worrying about key or array order. Detect missing, extra, an…
Real-time prompt injection and jailbreak detection for AI agents. Blocks instruction overrides, data exfiltration, tool poisoning and 8 attack types. Now with shared learning brain - confirmed attacks shared across the EMA network instantly. Grade A security for any AI pipeline.
- Discover available JSON document databases to identify which collections you can access for document management and querying operations.
- Discover available prompt engineering techniques with acceptance statistics to enhance AI interactions through optimized method selection.MIT
- Transform prompts using engineering best practices to improve clarity and effectiveness for AI assistants.
- Retrieve available prompt templates from the Open WebUI MCP Server to manage and utilize predefined AI interaction patterns for administrative tasks.MIT
- Discover available prompt templates, wizards, and workflows to streamline interactions with the Letta system.MIT
- Connect a JSON document database to cloud sync for sharing and collaboration across devices.
- Retrieve available prompt templates for AWS VPC Lattice to streamline documentation and management tasks, enhancing AWS networking workflows.
- Ask clarifying questions to understand user requirements and refine prompts for Claude Code engineering.MIT
- Create and manage document templates with variable substitution for automated documentation generation in coding sessions.
- Store JSON documents in a document database for persistent storage, enabling data management and retrieval within the MCP JSON Document Collection Server.
- Retrieve a JSON document from a database by specifying its unique ID. This tool accesses stored documents for viewing or processing within the MCP JSON Document Collection Server.
- Remove a JSON document from a database by specifying its unique ID, enabling document management and cleanup in Fireproof JSON databases.
- Retrieve prompt templates from Langfuse projects with filtering and pagination options to manage AI workflows.
- Find prompt templates for productivity automation by entering a search query to access reusable templates for tasks like planning, code review, and summarization.
- Browse available prompt templates by category to find reusable workflows for tasks like daily planning, code review, and document summarization.
- Remove a JSON document database from the MCP JSON Document Collection Server by specifying its name to manage storage and organization.
- Create a JSON document database for storing, managing, and querying structured data with cloud synchronization capabilities.
- Retrieve the JSON schema for video generation configurations to understand all available options, constraints, and structure before creating jobs.MIT
- Retrieve the complete JSON schema to define all configuration options for image generation jobs, ensuring valid and complete setups.MIT
- Browse and filter saved design templates in your Pictify account to discover reusable layouts for dynamic content generation before rendering images or PDFs.
- Convert 5D constellation coordinates into image-generation prompts for Stable Diffusion, ComfyUI, DALL-E, or Midjourney using three output modes.MIT
- Search AI prompt logs from medical document processing to track calls by type, document, status, date, or text content.MIT
- Retrieve available prompt templates with their metadata, including IDs, names, and descriptions, for managing LLM input configurations.
- Generate custom images from text descriptions using AI. Enter a detailed prompt to create visual content for various applications.MIT
- Discover available prompt templates from a target MCP server by specifying its location and transport type. Use this to explore what prompts a server provides for integration or testing purposes.MIT
- Extract content from Google Docs in text, JSON, or Markdown formats using document ID for integration and analysis.
- List all available Box Doc Gen templates for document generation with pagination support.MIT
- Retrieve available modifications for Orshot templates to customize image generation. Specify template ID and type to access editing options.MIT
- Retrieve HR document templates for offer letters, contracts, and policies with filtering options by category and status.MIT
- Retrieve all AWS Fault Injection Service experiment templates in a specified region to manage chaos engineering experiments.MIT
- Create versioned prompt templates with variable substitution for AI models in Portkey. Define templates, parameters, and function calls to standardize AI interactions.MIT
- Convert document content between Markdown, HTML, XML, and JSON formats to enable cross-format compatibility and processing.MIT
- Retrieve prompt templates by name from a markdown-based prompt management system for use in AI applications.MIT
- Updates user knowledge memory for Data Engineering concepts to personalize learning content and track progress.
- Generate images using pre-configured AI workflows for text-to-image and image-to-image tasks without managing complex JSON configurations.
- Generate Docker container configuration templates for containerization objectives using prompt-based templates in Cursor IDE.MIT
- Selects the best prompt candidate for a given context by balancing performance and diversity criteria, optimizing AI prompt effectiveness through evolutionary algorithms.MIT
- Structure text into JSON format using predefined templates with placeholders. Ideal for transforming unstructured input into organized, structured data for processing and analysis.MIT
- Generate JSON templates for Bitwarden Send objects to create secure file or text shares.MIT
- Create structured prompt templates for tasks like code generation and documentation by defining names, descriptions, and task types.MIT
- Lists available prompt templates for tasks like code review and API documentation generation in MCP Prompt Server.MIT
- Reloads prompt templates from the MCP Prompt Server to update available prompts for tasks like code review and API documentation generation.MIT
- Transforms structured JSON blocks into Claude-optimized XML prompts with token estimates for AI interactions.MIT
- Retrieve and filter deprecated run templates in ZenML workspaces. Use list_snapshots for modern pipeline management.MIT
- Load brand guidelines for AI content generation, providing identity, visual rules, voice constraints, and strategy in a single document.MIT