"Astro" matching MCP servers:

Provides unified natural language access to 40+ astronomical databases and surveys including DESI, SIMBAD, SDSS, and Gaia, enabling researchers to search, retrieve, and analyze astronomical data without learning complex APIs.

Enables access to Astro's App Store Optimization (ASO) database for analyzing app rankings, keyword trends, historical performance data, and app ratings. Provides comprehensive tools for tracking and comparing app store performance metrics through natural language queries.

Allows AI tools like Cursor, VS Code, Claude, ChatGPT, and Windsurf to access the latest Astro documentation in a structured way, enabling accurate answers about Astro's features, APIs, and best practices.

An MCP server that fetches, dedupes, and scores women's-health & FemTech research and industry news, designed to feed GitHub Agentic Workflows and an auto-updating Astro + RSS site.

Enables MCP clients to search and retrieve documentation from an Astro Starlight docs site by reading a pre-built catalog. Supports locale and version filtering, as well as structured data collections.

MCP server for Astro/Starlight docs sites, providing search, get, and list tools for documentation content.

Accurate astronomical catalog data and observing session planner for LLM assistants. Stops hallucinated magnitudes, coordinates, and visibility.

MCP server for managing and searching multi-tenant knowledge bases backed by SQLite with FTS5, enabling AI agents to persist and retrieve content via full-text search.

MCP server enabling AI agents to programmatically connect to and control Apache Superset instances, allowing users to manage dashboards, charts, databases, datasets, and run SQL queries through natural language interactions.

Web design analysis MCP server with 20 tools for layout extraction, motion detection, quality scoring, and semantic search. Uses Playwright, pgvector HNSW, and Ollama Vision to turn web pages into searchable, structured design knowledge.

Provides unified search and navigation across multiple project documentations via the Model Context Protocol (MCP). Any MCP-compatible agent can discover and retrieve knowledge from all indexed projects.

Enables AI-powered academic research workflow from keyword search to hypothesis generation. Integrates multiple AI models to automatically search ArXiv papers, extract key information, and generate innovative research hypotheses for researchers.