"Tools or platforms for generating basic images from text prompts" matching MCP servers:

Enables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.

Basic Memory is a knowledge management system that allows you to build a persistent semantic graph from conversations with AI assistants. All knowledge is stored in standard Markdown files on your computer, giving you full control and ownership of your data. Integrates directly with Obsidan.md

Provides a suite of deterministic tools for time calculations, math, and string manipulation that LLMs often struggle to perform accurately. It also includes utilities for secure randomness, data validation, and basic network operations like DNS lookups.

A simple MCP server built with FastMCP for experimentation and learning purposes. Includes basic web tools like article fetching and serves as a human-readable template for building custom MCP servers.

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.

A minimal MCP server for text processing, providing word count, uppercase conversion, and a summarization prompt template.

Enables AI assistants to register prompts for security verification, checking for hidden injections, data exfiltration patterns, and jailbreak attempts, then generate embed codes for displaying security badges on websites.

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

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.

A tutorial demonstrating how to build reusable, parameterized MCP prompt templates using FastMCP, including patterns for research, summarization, and code review.

A Model Context Protocol implementation for managing and serving AI prompts with a TypeScript-based architecture in a monorepo structure.

An MCP server that exposes any REST API to LLMs through runtime discovery, providing tools to browse endpoints, fetch schemas, and apply business rules without hardcoding or schema duplication.

Provides deterministic Unicode 17 text integrity operations—inspection, normalization, comparison, transcoding, security observation, difference explanation, indexing, and protocol profiles—over explicit strings and byte arrays via eight read-only MCP tools.

Lightweight MCP server for providing user prompts defined in Markdown with argument support.

A fully working MCP server built from scratch in plain Node.js, implementing tools, resources, prompts, notifications, and sampling according to the MCP specification, designed to connect to Claude Desktop or any MCP client.

A simple MCP server for utilizing prompts defined in YAML files.

Enables users to expose arbitrary HTTP APIs as configurable MCP tools by defining tool specifications in a JSON configuration file.

Enables clients to interact with a bundled documentation corpus through MCP tools and resources over HTTP or stdio, and provides a trajectory evaluation harness for grading agent performance.

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

A line-oriented text file editor. Optimized for LLM tools with efficient partial file access to minimize token usage.