"Information about the term 'Word'" matching MCP connectors:
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Live GPU compute & inference token price indices for AI agents — 591 reference indices across H100/A100/B200/B300 spot+on-demand, Claude/GPT/Llama token pricing, and more. Every value is methodology-versioned and citable via the /v1/verify handshake.
0bull Phone Farm is a remote HTTP MCP server for managing real physical iPhones. It covers posting accounts on TikTok, Instagram, and YouTube; video submissions; phone commands; raw touch input; screenshots; OCR; macros; GUI-agent tasks; and phone rental and billing flows. OAuth authorizes the user in a browser, and each call is scoped to the user's own accounts and phone grants. Phone-touching work is asynchronous because it runs on a real handset. The server returns an acknowledgement, then t
The official MCP server for Capawesome documentation and Capawesome Cloud.
The agent-native cloud: database, functions, AI, storage, computers. 50 tools, one API key.
A persistent Linux computer for your AI: what it installs and writes survives the session.
Publish the website you built with AI to a live public URL — straight from chat, no setup.
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.
Check if a repo will deploy, plan a deploy to your own cloud, and see status, logs and redeploys.
Search the Wraps docs and estimate AWS SES costs. Public, read-only, no authentication.
Docker Hub MCP — wraps the Docker Hub v2 API (free, no auth required for public data)
Deploy, pay for and manage apps on Flux Cloud, the decentralized cloud. Prices in USD.
The cloud for agents. Tools for AI agents to register, build, and deploy other agents. Zero human required.
Render Cost Calculator: the site's own MCP server — calculator, enquiry (enquiry = a human...
Compare live GPU cloud rental prices and match workloads to the cheapest provider.
Search AI capabilities across AWS Marketplace and the Official MCP Registry.
Unlock the power of DNS lookups with our DNS Lookup service using Google DNS-over-HTTPS. Whether
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.
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.
The Telnyx MCP server is an official implementation of the Model Context Protocol that enables AI clients (like Claude Desktop, Cursor, and OpenAI Agents) to interact with Telnyx's telephony, messaging, and AI assistant APIs. It provides comprehensive capabilities including making and managing phone calls, sending SMS/MMS messages, purchasing and configuring phone numbers, creating AI assistants with custom instructions, managing cloud storage buckets, scraping and embedding website content, and handling integration secrets. The server exists as both a local implementation and a remotely hosted version, allowing developers to integrate real-world communication infrastructure directly into AI applications.
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.