"General greeting or query" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
AI infrastructure design agent. Describe your app in plain English; Riley designs, prices, and deploys AWS or GCP infrastructure with generated Terraform.
Ask your AI assistant a cost question. Get allocation, correlation, and explanation in one response. Costory connects Claude, Codex, or Cursor to normalized cost data across AWS, GCP, Azure, Datadog, OpenAI, and Anthropic. https://costory.io Free trial 14 days, 250 USD / month up to 10M Spend
Provision, SSH into, run commands on, and manage Linux VPSes from an AI agent. Pay USDC over x402 (Base) or by card over HTTP 402, a running box in under 60s. No signup, no API key to buy. This remote endpoint offers free browse/discovery, quotes, and server status.
AI first app deployment, unlike lovable or figma make, webslop.ai lets you or your ai of choice setup node.js apps or static sites in seconds. Designed be be the perfect place for you to deploy websites and apps super fast to the rest of the world and has a generous free tier.
Deploy HTML or dist/ to a live HTTPS URL. No account. Drop, MCP, or CLI.
Query cloud, AI and SaaS spend across 25+ providers: costs, budgets, anomalies, unit economics.
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Hosting for AI agents: publish a live website in one tool call, ephemeral or forever.
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Live status for 172 cloud and SaaS vendors from their official feeds. Is it you, or is it them?
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The BigQuery remote MCP server is a fully managed service that uses the Model Context Protocol to connect AI applications and LLMs to BigQuery data sources. It provides secure, standardized tools for AI agents to list datasets and tables, retrieve schemas, generate and execute SQL queries through natural language, and analyze data—enabling direct access to enterprise analytics data without requiring manual SQL coding.
Create, manage, and query your Google Cloud SQL resources.
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.
- PuterOAuthcom.puter.mcp
Puter MCP lets your AI tools (Claude Code, Codex, or any other MCP-compatible client) interact with your Puter resources: managing files, publishing websites, deploying workers, and more.
Run, debug, and triage tests from your IDE using natural language, no dashboard switching, no manual data transfers. The TestMu AI (formerly LambdaTest) MCP Server is a single remote server exposing four tool suites: HyperExecute — analyze your project, generate YAML configs and test runner commands, then monitor jobs and sessions. Automation — pull a TestID's details plus command, network, and console logs into one chat for instant root-cause analysis. Includes mobile app upload. SmartUI — explain pixel, layout, DOM, and perceptual changes in a visual regression run, with context-aware React/HTML/CSS fixes. Accessibility — audit any public URL or a local React app against WCAG and get ready-to-apply remediation steps. Connects over https://mcp.lambdatest.com/mcp using OAuth 2.1 — no API keys in your config. One-click install in Cursor; works with Claude, GitHub Copilot, Cline, and any MCP client. Tests execute on the TestMu AI cloud: 3,000+ browsers and 10,000+ real devices.
