"Plotly Dash - A Python Framework for Building Interactive Web Dashboards" matching MCP servers:

Enables creating Plotly charts from natural language in Cursor, supporting a wide variety of trace types with full customization.

Provides tools to interact with the Dash documentation browser API, allowing users to list installed docsets, search across documentation, and enable full-text search.

Enables Large Language Models to access and manipulate Autodesk Revit models through a pyRevit-based bridge and the Model Context Protocol.

A MCP server that collects interactive user feedback during AI-assisted development, reducing unnecessary tool calls and costs by enabling AI to confirm with users.

Provides 12 tools to query South Korean building register data, including title sheets, floor details, and official house prices via the data.go.kr API. It enables users to perform smart building lookups and region code searches using natural language.

Enables AI to present options and launch an interactive web or terminal interface for user selection, then return the results to the AI.

A powerful MCP server that provides interactive user feedback and command execution capabilities for AI-assisted development, featuring a graphical interface with text and image support.

A powerful Model Context Protocol framework that extends Cursor IDE with tools for web content retrieval, PDF processing, and Word document parsing.

Exposes Dropbox Dash search and file metadata via STDIO, enabling users to search across company content and fetch detailed file metadata and content.

A lightweight and modular framework for building MCP-based file management systems with standardized module structure, flexible configuration, and extensible functionality registration mechanisms.

A framework for building MCP servers with built-in enterprise capabilities such as authentication, authorization, telemetry, audit logging, and data classification, allowing domain developers to focus on business logic while maintaining governance and compliance.

A middleware system that connects large language models (LLMs) with various tool services through an OpenAI-compatible API, enabling enhanced AI assistant capabilities with features like file operations, web browsing, and database management.

An MCP server for managing OpenSearch Dashboards, enabling AI assistants to create, manage, and inspect dashboards, visualizations, saved objects, and plugin features.

An intelligent server that transforms local Dash documentation into a context-aware assistant for Claude, providing developers with seamless access to documentation while coding.

Provides comprehensive building and office address information queries for enterprises in China, including fuzzy enterprise search, office address details and statistics, and building information queries to support geographical distribution and occupancy analysis.

Provides a production-ready FastMCP Python server boilerplate with structured logging, rate limiting, and config validation for building MCP servers compatible with Claude and other agents.

Enables AI agents to render interactive user interfaces such as forms, dashboards, charts, tables, and wizards directly in MCP-compatible clients. Supports structured data collection and richer interactions beyond text responses.

A Python MCP server for Metabase that enables AI assistants to query databases, manage dashboards, and interact with your Metabase instance.

A MCP server that enables human-in-the-loop workflow in AI-assisted development tools by allowing users to run commands, view their output, and provide textual feedback directly to the AI assistant.

Execute Python code via subprocess with timeout and error handling, returning stdout, stderr, and exit code.