"Generating a series of images using MCP from a sample image" matching MCP servers:

Fetches category data from a Q&A service API and returns a markdown summary grouped by category.

A TypeScript-based MCP server that implements a simple notes system, allowing creation and management of text notes with URIs and metadata.

A TypeScript-based MCP server that implements a simple notes system, allowing users to create, access, and generate summaries of notes via Claude Desktop integration.

A TypeScript-based MCP server implementing a simple notes system that allows users to create, access, and generate summaries of text notes.

Enables LLM clients to search a firm's precedent vault and draft grounded contract clauses, legal memos, and document summaries.

An HTTP MCP server that indexes large documents into exact-line-numbered sections, enabling AI models to locate, read, summarize, and edit parts of a document without ingesting the whole file.

Enables interactive AI chat through the Anthropic API, with document retrieval, slash commands, and extensible MCP tool integrations.

A Model Context Protocol server that implements a simple notes system, allowing users to create, list, and summarize text notes.

Enables natural language management of Gmail through MCP tools for searching, analyzing, summarizing, drafting, and sending emails, with AI reasoning and user confirmation for actions.

Provides various AI capabilities through DeepInfra's OpenAI-compatible API including image generation, text processing, embeddings, speech recognition, object detection, and classification tasks. Enables users to access multiple AI models for diverse tasks like generating images from prompts, transcribing audio, analyzing text sentiment, and performing computer vision operations.

A server that provides document processing capabilities using the Model Context Protocol, allowing conversion of documents to markdown, extraction of tables, and processing of document images.

Enables LLM clients to analyze numerical data series (NumPy, Pandas, Polars, lists) and receive token-efficient natural-language summaries of trend, volatility, anomalies, seasonality, and data quality instead of raw values. Supports single-series analysis, batch processing of multiple series, and structured JSON output.

Enables intelligent document processing by extracting text, classifying document types, and generating structured summaries from PDFs and images using vision LLMs.

Enables generating deterministic, cited research findings from caller-supplied source metadata and excerpts via a local-fixture MCP tool, supporting English and Spanish.

Enables local analysis of unstructured documents (PDF, DOCX, PPTX, SVG, PNG) by extracting text and structure with citation anchors, and verifies summaries against source material before a human approves saving a report.

Model Context Protocol server for Archive of Our Own: search fanfiction and have an AI read and rank fics for you.

A small MCP server that gives agents rich context about a YouTube video — its transcript, jump-to-the-moment deep links, metadata, and most-replayed moments — so they can answer questions, summarize, pull quotes, or surface highlights.

MCP server for evidence-based bullet point summarization guidance. Validates and improves bullet lists using scientifically-validated principles from cognitive psychology and UX research.

tooltrim reduces the tokens agents spend re-reading bloated tool results. Run it as an MCP server exposing compress and expand_tool_output, or as a gateway in front of any upstream MCP server: it re-exposes the upstream tools unchanged and shrinks each result (HTML/JSON/logs/tables) before it reaches the model, keeping the relevant content only.

Measures AI-detection risk in text and provides a line-by-line rewrite plan to lower the score.