"A tool for processing and extracting data from PDFs into structured formats" matching MCP servers:

Enables image processing tasks such as resizing, compressing, converting formats, cropping, and extracting metadata directly within IDEs like Cursor via the Model Context Protocol.

An enhanced MCP server that enables users to interact with NotebookLM while ensuring strict source fidelity and citation accuracy through client-side prompt structuring. It guides Claude to transform user queries into structured prompts that prevent the addition of external knowledge during document analysis.

Make it easy for agents to build their context about your projects over time The server provides a set of tools to help agents accumulate knowledge about a project over time in a structured way.

Enables LLMs to read and write local user data, generate fake users via sampling, and interact with structured prompts and resources.

Enables processing, validation, optimization, and analysis of 3D models with glTF/GLB support, including format conversion, compression (Meshopt/Draco), texture optimization, and detailed model statistics.

A personal MCP bridge that lets ChatGPT drive a local Codex CLI, translating instructions into Codex app-server threads and returning compact summaries of what Codex did.

Enables LLMs to perform addition calculations through a stdio-based MCP server with an add_numbers tool and type-safe validation.

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

A tool discovery MCP server that integrates with Azure DevOps wikis and code-graph-rag to match natural language goals to tools, enabling tool composition and proxy testing.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

An MCP server and CLI tool that transforms codebases into AI-ready context through semantic search, call graph analysis, and incremental indexing. It enables AI assistants to perform hybrid vector and keyword searches to understand complex repository structures and cross-file relationships.

A TypeScript Model Context Protocol (MCP) server to allow LLMs to programmatically construct mind maps to explore an idea space, with enforced "metacognitive" self-reflection.

Enables MCP clients to connect to a privacy-first, self-hostable workout planning and training log, allowing coaching agents to preview and apply program changes while accessing training data through OAuth-protected endpoints.

Provides a 'reflect' tool that creates cognitive checkpoints for AI assistants, forcing structured step-by-step reasoning through complex problems to improve accuracy and maintain context during task execution.

Provides agents with tools to score a page's AI readiness, check which AI crawlers robots.txt blocks, and assess passage citability—all performed locally.

Provides a unified MCP server to interact with multiple middleware (Loki, MySQL, Redis, RocketMQ, Elasticsearch, MongoDB) through a desktop application for connection management and configuration export.

Enables converting documents between formats over MCP: any supported input (docx, odt, xlsx, ods, pptx, odp, pdf) to structured Markdown, Markdown to docx, odt or pdf, direct cross-format pairs, and Markdown to sanitised HTML. Fidelity losses are reported rather than failing the conversion.

Extract structured data from any website with a simple SDK call. No scraping code, no headless browsers - just prompt and get JSON.

MCP proxy server with semantic tool search for LLM coding agents. It reduces context window usage by activating only relevant tools based on user queries.

Audits MCP tool descriptions for quality and reliability, scoring them 0-100, detecting smells, and providing rewritten versions for better agent accuracy.