"Tools for enabling LLMs to interact with web pages and perform end-to-end testing" matching MCP servers:

Enables deployment of HTML content, folders, and full-stack projects to EdgeOne Pages to generate publicly accessible URLs. It utilizes EdgeOne Pages Functions and KV storage for high-performance edge delivery of web applications.

Enables AI assistants to deploy and manage static websites on EdgeOne Pages via the Model Context Protocol.

Enables AI assistants to deploy and manage static websites directly through EdgeOne Pages. This self-hosted solution allows for direct file management and website hosting using EdgeOne's infrastructure and KV storage.

Enables AI assistants to deploy and manage static websites on EdgeOne Pages through a self-hosted MCP server. Supports one-click deployment, custom domain binding, and direct API access.

A self-hosted MCP server that enables AI assistants to deploy and manage static websites directly on EdgeOne Pages platform with KV storage support.

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

Enables AI assistants to deploy and manage static websites directly on EdgeOne Pages through a self-hosted Model Context Protocol solution. It simplifies web hosting by allowing natural language commands to handle site deployment and KV storage management.

A minimal MCP server template for deploying to Tencent Cloud EdgeOne Pages using Next.js and edge functions. Demonstrates tool registration and widget rendering with the hello_stat example tool.

Enables AI assistants to deploy and manage static websites directly on EdgeOne Pages. Simple self-hosted solution with one-click deployment and KV storage for website files.

Enables AI assistants to deploy and manage static websites directly through EdgeOne Pages. It provides a self-hosted solution for hosting website files using KV storage and managing content through the Model Context Protocol.

Enables AI assistants to deploy and manage static websites via EdgeOne Pages, with one-click deploy and API support.

Enables AI assistants to deploy and manage static websites through a self-hosted EdgeOne Pages MCP server, with one-click deploy and direct API access.

Enables AI assistants to deploy and manage static websites directly on EdgeOne Pages. Provides simple one-click deployment with KV storage for hosting website files accessible through custom domains.

An MCP server that enables LLM coding agents to deploy web applications to AWS serverless infrastructure, supporting backend, frontend, and fullstack deployments.

A service that enables rapid deployment of HTML content to EdgeOne Pages and automatically generates publicly accessible URLs for the deployed content.

Enables the deployment of HTML content, folders, and full-stack projects to EdgeOne Pages to generate publicly accessible URLs. It integrates with edge functions and KV storage to provide fast content delivery and supports custom domain configuration.

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

A Model Context Protocol server that provides AI assistants access to AWS CloudWatch Logs, enabling browsing, searching, summarizing, and correlating logs across multiple AWS services.

A governed MCP server enabling LLM agents to query BigQuery, inspect GCS, trigger Airflow DAGs, and run data-quality checks with built-in security guardrails like allow-lists, cost ceilings, and audit trails.

Enables AI agents to query multi-cloud costs, inventory, waste, and commitments across AWS, GCP, Cloudflare, and OVH through read-only MCP tools.

Enables MCP clients that lack built-in search — such as Claude Code through Bedrock or local LLM clients — to run web queries against Amazon's operated search index via a Gateway deployed in your own AWS account, with queries never leaving AWS and citation URLs preserved. Supports IAM/SigV4, Cognito, and API key authentication, per-gateway rate limits, IP and domain restrictions, and result filtering by domain and publication date.

Provides a Streamable HTTP MCP proxy for VS Code Copilot and Claude Code, using JWT client assertion to securely access NetSuite APIs.

Enables automated review and analysis of network security controls (AWS Security Groups, Network ACLs) using natural language queries. Supports NSC configuration reviews, network segmentation testing, and identifying security gaps through conversational LLM interaction.

Enables AI assistants to manage Coolify infrastructure including servers, applications, databases, deployments, and 80+ one-click services through 98 comprehensive tools for both cloud and self-hosted instances.

Enables read-only queries against a GCP PostgreSQL database, exposing tools to fetch recent users, user details by ID, and recent user activities without returning password or hash columns.

Enables AI assistants to deploy and manage static websites on EdgeOne Pages via a self-hosted MCP server. Supports KV storage and custom domain binding.

Publishes what an AI made — a page, a markdown or PDF doc, or a whole site — to a live HTTPS link. Runs locally over stdio from the @drop2run/mcp npm package, or hosted at https://mcp.dropto.run/mcp for chats that connect by URL.

Enables exploring Microsoft Fabric / Power BI workspaces and semantic models, and executing ad-hoc DAX queries.

An unofficial MCP server that connects AI assistants to Akamai APIs, providing tools for edge diagnostics, debugging, and network analysis.

An MCP server for managing and monitoring Docker, Docker Compose, and Kubernetes environments alongside Azure Application Insights. It enables advanced log filtering, container lifecycle management, and querying of cloud application traces and metrics.