"Bitbucket pull request reviewer information" matching MCP servers:

Enables LLM clients to access crop yield predictions from RGB imagery, topic-based PDF literature, and soil lab/moisture CSV data.

Enables AI agents to inspect and work with PDF files entirely on the local machine, covering page counts, metadata, layout, encryption permissions, scan-vs-text detection, and page rendering. Generated results land in a temporary workspace as short artifact ids that can be chained between tools and exported to real folders on request.

Enables MCP-capable chats and agents to generate images, video, and audio through OpenAI, Google Gemini, fal.ai, and Cloudflare Workers AI, optionally routed via Cloudflare AI Gateway. Supports image editing, asynchronous video jobs, and text-to-speech with per-request provider and model overrides, and can run over stdio or streamable HTTP.

Image tools for coding agents: generate from text, edit one reference image, remove backgrounds, upscale 2x, and create reference-based sprite animations. The MCP server, CLI and REST API share one key, credit balance and request history. Needs a DreamLayer API key and paid credits; sprite sheets are beta.

A read-only MCP server that exposes Tiramisu AI's product information, pricing, and official links to MCP-compatible AI clients.

Enables AI image generation, editing, and composition using Google's Gemini image models (Nano Banana Pro and Nano Banana). Supports text-to-image generation, multi-image composition, flexible aspect ratios, high-resolution output up to 4K, and real-time information grounding.

MCP server for GIF animation analysis. Provides metadata extraction, individual frame export, and per-frame timing information.

An MCP server that generates images using SenseNova U1 Fast API. Supports Chinese prompts, multiple resolutions, and generating up to 4 images per request.

Enables controlling a local Blender instance through natural language or code, allowing arbitrary Python/bpy execution and querying scene or object information via MCP.

Enables AI assistants to recognize and extract information from images via GLM-4V, supporting automatic screenshot recognition and MCP-based local image file reading for non-vision models like DeepSeek.

Exposes information about Z-Image AI image generation and editing platform, including styles, pricing, and official links, for MCP-compatible AI clients.

Enables web content extraction, screenshot capture, web search, arXiv paper search, and image search through Jina AI's APIs. Provides tools for reading URLs as markdown, searching the web for current information, and finding academic papers or images.

Enables AI assistants to remove backgrounds from images using the Poof API via URLs, file paths, or base64 encoding. It also allows users to monitor their account information and remaining credit balance.

Analyzes webpage screenshots to extract precise layout information by locating image assets and calculating spatial relationships, enabling AI assistants to accurately recreate layouts with proper semantic structure using computer vision.

Enables web searching via SearXNG, page content extraction with Crawl4AI, and image analysis using vision language models. It provides AI agents with tools for information synthesis and web-based data retrieval through OpenAI-compatible LLM endpoints.

A Model Context Protocol server that provides web and image search capabilities through Google's Custom Search API, allowing AI assistants like Claude to access current information from the internet.

Enables Claude to generate ByteDance Seedance videos and Seedream images through a BytePlus key, pricing every request in dollars before it is sent. It adds budget limits, ask-first approvals and whole-key spend tracking so costly generations cannot happen without consent.

Enables comprehensive video file analysis including extracting metadata, stream information, bitrate calculations, and generating technical reports. Supports all FFmpeg-compatible video formats with output in JSON, text, or Markdown formats.

A Pinterest Model Context Protocol (MCP) server for image search and information retrieval

Enables extraction of design context from Figma files as CSS-like properties and provides tools to render Figma nodes as images. It integrates with AI agents via the Model Context Protocol to facilitate design-to-code workflows by providing layout, style, and typography information.