"Automated PDF Processing Server with AI Workflow and Payment Integration" matching MCP servers:

An MCP server that converts Markdown files containing Mermaid diagrams into PDF documents by rendering diagrams as SVG images. It provides a specialized tool to automate document conversion while ensuring all visual charts are correctly embedded in the final output.

Monitor failing GitHub Actions workflows, auto-fix them with OpenCode, and retry the run — driven by a workflow_run webhook, coordinated through an MCP server.

Enables AI assistants to use Neo4j knowledge graphs and Qdrant vector databases for hybrid reasoning, combining structured facts with semantic search for advanced knowledge management, research analysis, and standardized coding workflows.

LFWin Payment MCP Server is a payment capability service for AI Agents. Adhering to the standard MCP protocol, it exposes capabilities including creating payment orders, checking payment status, initiating refunds and querying refund status for Cursor, Cline, Claude Desktop, enterprise intelligent assistants and self-developed Agent applications.

Enables PDF processing and analysis including text extraction, metadata retrieval, search, page manipulation, splitting/merging, conversion to images, and form handling.

Enables AI agents to integrate the SIBS payment gateway, providing tools for creating checkouts, checking payment status, issuing refunds, and generating Multibanco references directly through natural language.

A Model Context Protocol server that exposes AI workflow templates as callable tools, enabling MCP clients to list templates, inspect their input/output schemas, and execute them synchronously or asynchronously to get structured results.

Enables an AI assistant to author algorithm storyboards, workflow maps, and UI styling through MCP, serving a local web app for visualizing and reviewing them.

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

Guides agents through structured workflows with predefined steps, allowing for flexible execution via instructions and tool calls.

Implements a secure MCP server with API Key and JWT authentication, providing tools like echo, login, secure_action, and admin_action. Includes MCP Inspector integration for testing and debugging.

Enables uploading, arranging, merging, and downloading PDFs through an MCP-compatible LLM client by interacting with a PDF Merger API.

A lightweight, powerful, and flexible workflow engine that executes tasks defined in YAML configuration files.

Enables precise extraction of PDF content, including text coordinates, vector shapes, images, and on-demand raster rendering, for use cases like reconstructing design files.

Enables AI assistants to natively read, edit, and redact PDF documents in place through MCP tools, eliminating manual script execution and layout issues.

A local-first MCP server that ingests PDFs, extracts structure, and provides semantic search and sequential navigation tools for AI clients to query and learn from documents.

Turn markdown into designed PDFs with cover page, table of contents, and code blocks that hold across pages. One command from Claude Desktop, Claude Code, Cursor, Cline, Zed, or any MCP-capable client.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

An MCP server for reading, rendering, and searching PDF files, specifically optimized for LLMs to extract text, tables, and technical diagrams. It enables metadata retrieval, multi-format text extraction, and page-to-image rendering using PyMuPDF.

Architecture diagram with concurrency capacity and bottleneck estimates from any codebase.