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

Enables searching and accessing Dash documentation directly, with tools to list docsets, search snippets, load pages, and enable full-text search.

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

Contract-driven test enforcement and reporting for LLM-generated code via MCP, VS Code, Copilot CLI, Claude, Cursor, or Python SDK.

Exposes the SiftingIO market-data SDK to AI assistants, enabling live prices, fundamental data, and market information retrieval.

Enables LLMs to query live data from over 250+ sources via CData Python Connectors using natural language. Wraps connectors as a Model Context Protocol server.

Enables secure execution of Python code in a sandboxed WebAssembly environment using Pyodide and Deno. Automatically handles package management and captures complete execution results including stdout, stderr, and return values.

Enables web research through multi-provider search, documentation lookup, public code search, and clean Markdown extraction from static or JavaScript-rendered pages via five read-only tools.

Ultra-lightweight headless browser for AI agents. Provides MCP tools for navigating URLs, extracting structured content, and building autonomous agent workflows.

MCP server that parses web pages into clean markdown via Crawl4AI's HTTP API, exposing parse_page and health-check tools with configurable proxy and timeout.

Enables AI assistants to fetch public web pages as readable text or HTML, with caching, live refresh, and parallel job handling.

Implementation of an MCP server for the RAG Web Browser Actor. This Actor serves as a web browser for large language models (LLMs) and RAG pipelines, similar to a web search in ChatGPT.

A Machine Comprehension Protocol server that enables AI assistants to interact with Kestra workflows through natural language, supporting operations like flow management, executions, backfills, and other Kestra features.

An MCP server for securely executing Python code, supporting STDIO, Streamable HTTP, and SSE transports, with easy deployment on Heroku.

Enterprise-grade MCP server integrating Claude AI capabilities, enabling AI-powered conversations, file operations, and system tools via the Model Context Protocol.

Model Context Protocol server to run Python code in a sandbox.

Enables coding agents to drive a real Playwright-backed browser session, navigating, observing, interacting, and capturing proof on web pages via MCP tools across stdio and Streamable HTTP transports.

A client-side MCP proxy that injects OAuth 2.0 bearer tokens or API keys into MCP requests, enabling MCP clients to connect to OAuth/API-key-protected MCP servers like Amazon Bedrock AgentCore Gateway. It automatically fetches and refreshes credentials using AgentCore Identity or static values.

Enables searching and retrieving content, module information, and Twig template snippets from a-blog cms via its GET API.

Enables AI assistants to directly control and interact with the Unreal Editor through natural language, allowing tasks such as spawning actors, building levels, creating materials, and running Python scripts.

Enables autonomous agents to inspect live web pages, prune noisy DOM content down to semantic essentials, and bind each form field to agent state by matching input attributes, autocomplete hints, and regex validations. It also converts HTML/Markdown tables into type-inferred JSON records and scores agent action trajectories for precision, recall, and edit distance.