"A tool for generating and live previewing Mermaid diagrams from code" matching MCP servers:

A local MCP server for Cursor that converts Markdown files and Mermaid diagrams to JPEG images with configurable dimensions and quality.

Enables AI agents and users to render Mermaid diagram code blocks into embedded SVGs within Obsidian notes locally, while preserving reversible synchronization with sidecar .mmd files.

Encoding-aware, indentation-smart file tools for AI coding agents. 20+ tools including read/edit with automatic encoding detection, smart indentation conversion, SSH, SFTP, process management, and system utilities.

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.

Converts Markdown files and raw content into professionally styled PDFs with full support for Mermaid diagrams and syntax highlighting. It offers customizable page formats, margins, and modern typography for high-quality document generation.

50 tools and 400 functions for working with Excel/.xlsx spreadsheets — read/write, recalculate formulas, diff, repair broken references, and audit. Built for AI agents.

An MCP server that exposes macOS Spotlight search as tools, wrapping mdfind and mdls to provide full-text and metadata file search across the system.

An experimental MCP server that enables AI assistants to interact with VS Code workspaces through file operations, code execution, and Git management. It also provides tools for Docker integration, project scaffolding, and secure command execution using project-specific configurations.

A comprehensive MCP server that provides AI assistants with tools for file system management, Git integration, and shell command execution. It features specialized code utilities for analysis, formatting, and linting to enhance development workflows within Claude Desktop.

Enables file reading with pagination and regex-based code search across a codebase using grep.

Enables Claude AI to run terminal commands, perform file operations, and manage git in a project directory via the Model Context Protocol.

Local MCP server enabling Codex and ChatGPT to read/write files, execute commands, manage processes, use Git, and inspect images on the user's machine with full privileges.

Enables local OCR transcription of images using tesseract.js, with optional low-token AI-generated descriptions, folder batch processing, and compatibility with MCP clients like ChatGPT, Claude, opencode, and Cursor.

A read-only remote MCP server that searches and reads files from a personal Microsoft OneDrive folder via Cloudflare Workers, enabling live access without a local workstation or tunnel.

A collection of small MCP servers for macOS automation that expose Apple Mail, MoneyMoney, and Spotlight functionality as tools via AppleScript and command-line, enabling AI applications to search mail, manage contacts and transactions, and perform system-wide file searches through natural language.

An MCP server that enables file system search and inspection, including directory listing, regex-based file name and content searches, and reading text, PDF, and DOCX files.

A secure, production-grade MCP server that provides filesystem operations, AST math evaluation, and system diagnostics for LLM agents.

Enables document conversion between PDF, DOCX, and Markdown formats to facilitate reading and editing complex files in AI tools like Claude Desktop or Cursor. It utilizes marker-pdf and pandoc to provide structured text versions of documents, helping to manage context and support unsupported file types.

A modular, extensible MCP multi-server hub that gives LLMs sandboxed file access, Git operations, web fetching, and persistent memory, deployable via Ansible.

A TypeScript prototype for an MCP-style registry providing local utility tools for shell command execution, filesystem access, and search functionality. It features Zod input validation and project manifest resource exposure for embedding into larger MCP implementations.