978 Model Context Protocol servers — searchable, rated, ready to install.
Multi-cloud cost, inventory and waste analysis over MCP: AWS, GCP, Cloudflare and OVH.
Deploy and manage websites and apps on Swiss hosting, with HTTPS, from your AI agent.
A persistent Docker or Fly computer with a Three.js interface and optional live Xfce desktop.
Debug background jobs — runs, traces, spans, schedules, queues and deployments.
Order, configure and deploy Docker containers and PostgreSQL or SQL Server databases in the EU.
Read-only SQL across your PostgreSQL, MySQL, S3 buckets and local data files, in one query.
Official Backblaze B2 MCP server for buckets, files, keys, Object Lock, and S3 storage.
Host apps built with AI: deploy to a live HTTPS URL, custom domains, secrets and backups.
Deploy websites; manage apps, persistent app volumes, VMs, S3, NAT gateways and load balancers.
MCP server for the Google Apps Script API: projects, code, versions, deployments and executions.
AI product expert answering from live source code, with sources and a verification status.
Manage Percona PostgreSQL + PgBouncer on Kubernetes — safe-by-default access modes and guards.
Create, validate, simulate and deploy Camunda 8 BPMN processes, forms and DMN from an agent.
Guardrailed fleet ops for AI agents: multi-cluster Kubernetes via OCM with policy, approval, audit.
Hosts, metrics, Docker and authorized_keys over a macOS terminal's live SSH connections
Build LumenJS apps, use the Roxyon BaaS, and deploy apps and web projects to Roxyon infrastructure.
List Civo instances, Kubernetes clusters, networks and DNS; reboot instances, add rules.
Search logs, investigate errors, check deployments, and monitor uptime for your elmah.io org.
Simulate cloud infrastructure and estimate cost before deploying or changing infrastructure.
Build, test, deploy and run AI phone agents: agents, numbers, calls, tests, knowledge, campaigns.
MCP server for Azure Service Bus. Peek, search and replay dead-letter messages from any MCP client.
Build a working web app from a prompt, then deploy it to a live URL.
Search the Cerebrium docs: deployment, cerebrium.toml, hardware, endpoints. Also sends feedback.
Give your AI a place to publish: living pages with live data, shareable links, no deploy pipeline.
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