"Linux-compatible version of Cursor" matching MCP connectors:
Matching Connector Tools:
Official Kudosity Model Context Protocol (MCP) server that allows AI-powered editors (like Cursor and Windsurf) and assistants (like Claude Desktop) to directly explore and execute Kudosity APIs. With MCP, your AI can search API specs, generate code snippets, and run live requests; all without leaving your development environment.
Provides a platform-agnostic specification of the technical features every decent website should have
Changelogs for apps, games and operating systems. Ask what shipped since the version you run.
APIs.guru MCP — keyless directory of 2,500+ public APIs and their OpenAPI specs.
Read-only discovery of Framekeep capabilities, security boundaries, and public resources.
Linux package, file, command, vulnerability, lifecycle, migration, and repository intelligence.
Engineering log of self-hosted AI on NVIDIA DGX Spark (GB10/SM121A). 60+ articles indexed.
Evidence-based register of known Copilot Studio errors and limits, with dated, human-verified fixes.
An MCP server that gives your AI access to the source code and docs of all public github repos
Sixteen years of API research as MCP tools — stories, areas, governance blocks & services
Official MCP server for UploadKit, the file-uploads platform for developers. Gives Claude Code, Cursor, Windsurf, and Zed first-class knowledge of UploadKit's 40+ open-source React components, Next.js route handler scaffolding, <UploadKitProvider> wiring, BYOS (S3/R2/GCS/B2) configuration, and full-text search across 88+ docs pages. Runs locally via npx — no API key, no telemetry, no config.
Search and retrieve articles from the Sovereign AI Blog. A practical engineering log of self-hosted AI on NVIDIA DGX Spark with articles covering SGLang, Mistral, Voxtral, OpenClaw. Tools: search_blog, get_article, diagnose_sglang. Endpoint URL: https://mcp.sovgrid.org/self-hosted-ai?ref=smithery Transport: streamable-http (oder „HTTP Streaming") Tags/Categories: knowledge-base, search, self-hosted-ai, sovereign
The AWS Knowledge MCP server is a fully managed remote Model Context Protocol server that provides real-time access to official AWS content in an LLM-compatible format. It offers structured access to AWS documentation, code samples, blog posts, What's New announcements, Well-Architected best practices, and regional availability information for AWS APIs and CloudFormation resources. Key capabilities include searching and reading documentation in markdown format, getting content recommendations, listing AWS regions, and checking regional availability for services and features.
MCP server for the RPG-Schema.org definition and helping the usage of RPG-Schemas in TTRPG manuals
VibeMarketing (https://vibemarketing.ninja/mcp) is a directory service that catalogs and provides information about various MCP (Model Context Protocol) servers. It serves as a centralized resource where users can discover different MCP servers and their capabilities. Examples of servers listed in the directory include Sequential Thinking MCP (for dynamic problem-solving through structured thought sequences) and Memory MCP (a knowledge graph-based persistent memory system).
Give your agents trusted access to a company's living documentation. Search, read, and update source-of-truth knowledge across engineering docs, runbooks, decisions, code context, and team knowledge. `https://falconer.com/mcp
Team docs served to AI agents over MCP - search, Markdown reads, version pinning, read audit.
A cited wiki of your GitHub repo: search, read pages, find symbols and ask, with line citations.
TradesPro is an open source MCP server that gives AI assistants structured knowledge of the skilled trades: electrical (NEC 2023), plumbing (UPC 2024), and HVAC (IRC Mechanical).
LLMtoMD is the memory layer for AI coding agents. It converts any document — PDF, DOCX, slides, spreadsheets, images, audio, even whole websites — into clean, structured Markdown, then exposes it over MCP so your agent can search your FRDs, specs, and API docs on demand instead of re-reading (or forgetting) them.