How do I install the Release Dbt MCP skill?

Run npx skillmds@latest add tomevault-io/release-dbt-mcp in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

What does the Release Dbt MCP skill do?

Release a new version of dbt-mcp to PyPi Use when this capability is needed. It is listed under AI & ML on SkillMD.

Is Release Dbt MCP safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Release Dbt MCP?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Release Dbt MCP free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Release Dbt MCP?

tomevault-io (@tomevault-io) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Release Dbt MCP by tomevault-io — Agent Skill

Name: Release Dbt MCP
Author: tomevault-io

File contents

Initiate the Create release PR GitHub workflow. Use the auto for the bump input. Don't set the prerelease input.
Wait for this to start and then poll the status of this running workflow.
Once it finishes successfully, approve & squash merge (gh pr merge --squash --admin) the PR that was created. This repo does not allow merge commits. This is an autogenerated PR, so it is okay to bypass CI. This is the only case that bypassing CI is okay.
Merging this PR will kick off the Release dbt-mcp workflow.
Wait for this to start and then poll the status of this running workflow. When the workflow waits for GitHub environment approval, open the page with open <url>
Ask the user to continue once they have approved the GitHub environment.
Once the user continues, continue polling the status of the Release dbt-mcp workflow.
When that workflow has finished successfully. Ensure that the new version of dbt-mcp is on PyPI by checking the JSON API at https://pypi.org/pypi/dbt-mcp/json (the HTML page is JS-rendered and won't work with WebFetch).
Report to the user the status of all GitHub workflows that ran and the status of the release.

Source: dbt-labs/dbt-mcp — distributed by TomeVault.

Frequently asked questions

Release Dbt MCP