mcp server
io.github.AkaciaNL/basicdeploy-mcp
The runtime your agent deploys to — DB, storage, and a public URL in one MCP call.
Description as published by the maintainer. Source
- version 1.0.6
- active
- retrieval
active — Most recent push to the repository was 2026-08-06. Dashed tags are derived by ZBS Index from the published description, not stated by the maintainer.
Signals
These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.
| Signal | Value | What it measures | Window | Observed | Source |
|---|---|---|---|---|---|
| GitHub stars | 0 | Number of GitHub accounts that bookmarked this repository since it was created. It is a bookmark count, not installs, not active users and not quality. | cumulative, all time | GitHub | |
| Last commit | 2026-08-06 | Date of the most recent push to any branch. This is the strongest cheap indicator of whether the project is still maintained. | point in time | GitHub | |
| Open issues | 0 | Open issues plus open pull requests, as GitHub counts them together. A high number can mean an active project or an abandoned one. | as of fetch | GitHub | |
| Latest published version | 1.0.6 | Latest version string the maintainer published to the registry. | as of fetch | Model Context Protocol | |
| Registry record last updated | 2026-08-06 | When the registry record was last updated by its maintainer. | point in time | Model Context Protocol | |
| License | MIT | Licence GitHub detected in the repository. Detection can be wrong; the LICENSE file is authoritative. | as of fetch | GitHub | |
| First listed in the MCP Registry | 2026-08-06 | Date this server was first published to the official MCP Registry. Not a usage or quality measure. | point in time | Model Context Protocol | |
| repository status | active | The repository exists on GitHub and is not archived. This says nothing about how recently it was worked on. | as of fetch | GitHub |
Where to get it
Related, by what their authors tagged them
-
OBTO
— last commit 2026-08-05, shares paas
Your AI builds, deploys, and runs full-stack apps on a hosted workspace created at first sign-in.
-
Arcane RMCP
— last commit 2026-08-05, shares containers
Rust MCP server and CLI for Arcane Docker and container management.
-
Arcane RMCP
— last commit 2026-08-05, shares containers
Arcane Docker and Compose management over MCP and CLI with authenticated stdio and HTTP.
-
Tidesman
— last commit 2026-07-18, shares containers
A free native MCP server for running and debugging Linux containers with Apple's container tool.
-
Control Plane
— last commit 2026-08-05, shares containers
Control Plane (controlplane.com): deploy and operate workloads across AWS, GCP, Azure, and more.
-
io.github.alisaitteke/docker-mcp
— last commit 2026-01-27, shares containers
MCP server for managing Docker containers, images, networks, volumes, and registries
-
io.github.containers/kubernetes-mcp-server
— last commit 2026-08-06, shares containers
A Model Context Protocol (MCP) server for Kubernetes and OpenShift
-
ai.dataecho/mcp
— last commit 2026-07-04, shares deployment
Deploy files, sites, and Dockerfile apps to live URLs + private drives for agent memory.
-
be.vibedeploy/vibedeploy
— last commit 2026-08-06, shares deployment
Deploy and host AI-built websites on EU infrastructure, straight from your AI agent.
-
glitternetwork-pinme-pinme
— last commit 2026-07-25, shares deployment
Use this skill when the user mentions "pinme", or needs to upload files, store to IPFS, create/publish/deploy websites…
These share tags the maintainers applied themselves, such as paas, containers, deployment. Common tags like "mcp" or "ai" are ignored for this: agreeing with six hundred other projects is not a similarity.
This is not a recommendation and not a test result. It is a map of what the authors said their work is about.
How the author describes it
Topics the maintainer set on GitHub: ai-agents, claude, containers, cursor, deployment, mcp, model-context-protocol, paas.
Bring your own setup
We take apart real AI setups every week and show what broke, what cost too much, and what the trace actually said. If you run agents on real work, that is where the useful conversation is.
Join ZBS AI Practice Lab