qbash Connectors / DigitalOcean

DigitalOcean MCP serverand Python AI tasks

qbash hosts a DigitalOcean MCP server you can use in Claude, ChatGPT, Codex, Cursor, Grok Bot and Muse.

Developers use qbash Tasks to write cloud-hosted Python functions that pair DigitalOcean with models such as Claude and GPT.

Connect DigitalOcean free

MCP server

Build a DigitalOcean MCP server

Give ChatGPT, Claude and your other AI tools access to DigitalOcean through one server. You pick which DigitalOcean tools it shares, and you can add other connectors, memory folders and Tasks to the same server.

How to set it up

Connect DigitalOcean on the qbash Connectors page.
Create an MCP server and add the DigitalOcean tools you want to share.
Paste the server URL into your client. It connects with OAuth or an access token.

Connect a client Package an MCP server

Python AI task

Write a DigitalOcean task in Python

A qbash Task is a hosted Python function that calls DigitalOcean and AI models.

Find the failing step in an App Platform build

Read the build logs of one deployment and pass them to an inline prompt, which quotes the error and suggests a likely fix.

main.py
report = qbash.integrations.digitalocean.get_deployment_logs(
    app_id="4f6c71e2-1e90-4762-9fee-6cc4a0a9f2cf",
    deployment_id="b6bdf840-2854-4f87-a36c-5f231c617c84",
    log_type="BUILD",
)
logs = report.get("logs", "")
if logs:
    diagnosis = qbash.ai.run_prompt(
        slug="digitalocean-build-failure",
        variables={"logs": logs},
    )
    qbash.output({"diagnosis": diagnosis, "truncated": report.get("truncated", False)})
else:
    qbash.output("This deployment returned no build logs.")

Sample get_deployment_logs response

{
  "status": "success",
  "logs": "web 2026-10-14T09:12:03Z [build] -----> Installing dependencies\nweb 2026-10-14T09:12:41Z [build] npm error code ERESOLVE\nweb 2026-10-14T09:12:41Z [build] npm error Could not resolve dependency: peer react@\"^17.0.0\" from example-widget@2.1.0\nweb 2026-10-14T09:12:42Z [build] ERROR: failed to build: exit status 1\n",
  "truncated": false,
  "url_count": 1,
  "deployment_id": "b6bdf840-2854-4f87-a36c-5f231c617c84"
}

What the DigitalOcean connector can do

Read App Platform deployments and their build, deploy or run logs
Redeploy an app or change its spec and environment variables
Check Droplet status and metrics, and reboot or power-cycle a Droplet
Create, update and delete DNS records
See month-to-date usage and past invoices
Inspect managed databases and Kubernetes clusters
List, download, upload and delete files in Spaces buckets

See all 30 DigitalOcean methods in the SDK Reference

qbash Tasks: AI applications in Python

A Task is a Python function that calls DigitalOcean, your other connectors and models such as Claude, GPT, Gemini and Grok. qbash hosts and runs it.

Run Tasks on a schedule or from your team's tools

+ more

Deterministic where it counts Write the logic in Python and call a model only for the steps that need judgement, so the rest runs the same way every time.
Version controlled Every save is a revision you can compare and roll back.
Logged Each run records its inputs, output, errors and what started it.
Shared credentials Connections belong to your organization, so a Task keeps working when its author is away.

qbash Tasks Python AI SDK

DigitalOcean MCP questions

Does DigitalOcean have an official MCP server?

Yes. DigitalOcean publishes its own MCP server, documented at docs.digitalocean.com/reference/mcp and also available as the @digitalocean/mcp package. The qbash server sits on the same URL as your other qbash connectors, and a scheduled Python task can make the same calls.

Which token scopes does the connection need?

Custom scopes for the resources you plan to use, plus account:read, which qbash calls to check the token when you save it. The Spaces tools also need a Spaces access key, secret key and region on the same connection.

Can an AI client see database passwords or app secrets?

Database tools return engine, version, status, size and host with credentials removed. get_app_spec does return an app’s environment variables, so add it to a server only when everyone on that server may read them.