"SearXNG - Open Source Metasearch Engine" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Kaiva Bridge turns your API, database or documents into a managed MCP server for Claude, ChatGPT, Cursor and VS Code. Point it at an OpenAPI or Swagger spec, an API docs link, a cURL command, a Postman collection, a GraphQL endpoint, Postgres, MySQL, MariaDB or SQL Server, spreadsheets, PDFs and other documents, or an MCP server you already run. Bridge reads the source and proposes tools, and you choose which ones your AI client sees. No code to write and nothing to run. Connect this server and your agent does the setup for you: it lists your servers, shows one, drafts a new server from an OpenAPI spec, and refreshes a server's tools when its API changes. Free plan: 10 servers and 200,000 tool calls a month, no credit card. Pricing: https://kaiv.ai/bridge/pricing Security: https://kaiv.ai/bridge/security Docs: https://kaiv.ai/bridge/docs
Connect Claude, ChatGPT or any MCP client to your turbopress hosting account. Ask in plain language how your website is doing, how much disk space is left, which invoices are open or when a domain expires. The answers come straight from your customer account, without logging into the panel. Beyond answering questions, the server can make changes for you: create mailboxes, renew SSL certificates and more. Your AI client asks for confirmation before any change, and you can revoke access at any ti
Give AI agents a real cloud Chrome: open sessions, navigate, read pages, click, type and screenshot.
Zero-Ops deploy of a private AI workspace to your own VPS — from your AI chat. Free and open-source.
The Google GKE MCP server is a managed Model Context Protocol server that provides AI applications with tools to manage Google Kubernetes Engine (GKE) clusters and Kubernetes resources. It exposes a structured, discoverable interface that allows AI agents to interact with GKE and Kubernetes APIs, enabling them to inspect cluster configurations, retrieve Kubernetes resource YAMLs, monitor operations like cluster upgrades, diagnose issues, and optimize costs—all without needing to parse text output or use complex kubectl commands.
The Google Compute Engine MCP server is a fully-managed Model Context Protocol server that provides tools to manage Google Compute Engine resources through AI agents. It enables capabilities including instance management (creating, starting, stopping, resetting, listing), disk management, handling instance templates and group managers, viewing machine and accelerator types, managing images, and accessing reservation and commitment information. The server operates as a zero-deployment, enterprise-grade endpoint at https://compute.googleapis.com/mcp with built-in IAM-based security.
Website hosting for AI agents. Build, preview and publish websites from your agent: typed React source built through a quality gate into private drafts you approve, live URLs on webly.site or your own domain, version history and rollback, forms and analytics. Publish without an account and claim the site later.
Which open models fit your GPU or Mac, measured. Model momentum, GPU rental prices, weekly pick.
Generate and run high performance queries on open and private spatial data at-scale in the cloud
AI data-center design engine: size, validate & lay out Rubin-era data centers. Korea live.
Deploy open-source services and your own apps on Open Source Cloud (OSC, osaas.io).
Publish an app your AI agent built, then choose who can open it, like sharing a doc.
Your AI Agent's Infrastructure Layer. Connect Claude, Copilot, Codex, or ChatGPT to 200+ managed open source services. Start databases, pipelines, and applications through natural language.
Manage Rivet Cloud namespaces and actors, run Code Mode, and open the Rivet Actor Inspector.
Deploy containers on Kubernetes with x402 billing. 9 workload types and source builds.
Cloudflare Workers MCP server: agent-workflow-engine
The OpenMesh MCP Server provides decentralized, permissionless cloud infrastructure that integrates AI assistants with Web2 and Web3 applications without middlemen. It offers intelligent service discovery to identify MCP servers, acts as a universal proxy for routing requests to discovered services, implements performance optimization through usage feedback, and provides automatic fault tolerance with alternative services when servers become unavailable.
