"author:pinkpixel-dev" matching MCP servers:

Generates and edits images using OpenAI GPT Image or Google Gemini models, saving every result to disk and returning local file paths so AI assistants can continue working with the images. It enables prompt-based image creation, editing, inpainting, multi-image composition, and model listing through MCP tools.

MCP server that allows AI agents to fetch and process llms.txt documentation from various sources. Fetch documentation from any HTTPS URL and automatically convert HTML content to readable markdown.

A Model Context Protocol server enabling AI assistants to scrape web content with high accuracy and flexibility, supporting multiple scraping modes and content formatting options.

Nectar is a stdio MCP server for Pollinations image and video generation. It gives MCP clients a small, focused toolset for generating images, editing images, generating videos, listing available image/video models, and checking pollen balance.

An MCP server that gives LLMs direct access to OpenRouter's Image API to generate images, edit/transform existing ones, and browse the model catalog.

A flexible memory system for AI applications that supports multiple LLM providers and can be used either as an MCP server or as a direct library integration, enabling autonomous memory management without explicit commands.

A task management server that helps AI assistants break down user requests into manageable tasks and track their completion with user approval steps.

Gives AI agents a local-first, persistent memory backed by a single SQLite file, letting them save decisions, preferences, and facts, then recall them by meaning or keyword across sessions and projects. Exposes tools for loading pinned context, searching, adding, updating, listing, and deleting memories, so agents stop forgetting between sessions.

An AI router that connects applications to multiple LLM providers (OpenAI, Anthropic, Google, DeepSeek, Ollama, etc.) with smart model orchestration capabilities, enabling dynamic switching between models for different reasoning tasks.