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Your coding agent already writes the code. With Ankra connected, it can also see whether that code passes CI, read why it failed, and fix it. No copying logs out of a web page, no guessing which step broke. Two things make that work, and you want both:
  • The Ankra MCP server gives the agent live data: validate a pipeline, convert a workflow, watch a run, read a step’s log, request merge when green.
  • The Ankra skills teach the agent how Ankra pipelines work: the stage kinds, the authority rules, caching, fast CI. It then writes a pipeline that validates the first time instead of a GitHub Actions workflow.
The agent can also run the ankra CLI in its terminal, which covers everything the MCP tools do not, such as starting a run.

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The loop your agent runs

The agent never needs your CI provider’s web page, and you never paste a log into a chat.

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Set up

1

Connect the Ankra MCP server

Start Claude Code, run /mcp, select ankra and choose Authenticate. Sign in, pick your organisation and approve. mcp:read is enough to validate, convert and watch. Grant mcp:write only if you want the agent to request merge when green.
2

Install the Ankra skills

The skills land in ~/.claude/skills, with the /ankra-* workflow commands in ~/.claude/commands. Claude Code picks the right one from what you ask. ankra-ship and ankra-cicd cover pipelines.
3

Check it works

Ask: “Validate .ankra/pipeline.yaml with Ankra.” Claude Code should call cicd_validate_pipeline_yaml and report ok, warn or fatal.

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Prompts that work

These are written for an agent with the MCP server connected and the skills installed. Replace my-org/my-repo with your repository.
This repository has no CI yet. Write an .ankra/pipeline.yaml that tests on every pull request and push to main, caches dependencies, and builds, scans, gates and publishes the image on push. Validate it with Ankra before you show me.
The ankra-cicd skill steers the agent to the right stage kinds, network tiers and cache directories. cicd_validate_pipeline_yaml catches anything wrong before you commit.
Convert everything under .github/workflows into one Ankra pipeline. Keep the matrix and the Postgres service. List every step you could not convert, and delete the workflow files in the same change.
The agent calls cicd_convert_workflow_to_pipeline, which returns the pipeline plus notes for every step it could not map one to one.
Push this branch, watch the Ankra pipeline for my-org/my-repo, and if it fails, read the failing step’s log, fix the cause and push again. Stop after three attempts and tell me what you changed.
watch_pipeline_run returns the failing step and a log tail. get_pipeline_step_logs gets more of the log when the tail is not enough.
Our pull request runs take too long. Add affected: to the Go and pnpm test stages, path sets for the components, and caches where they are missing. Show me with ankra pipeline validate —changed-file which stages a change to web/ would skip.
The agent edits the pipeline and runs the CLI to prove the plan, as described in Fast CI.
Request merge when green for my-org/my-repo pull request 412.
This needs mcp:write and a connection in Agent mode. Ankra merges only when the pipeline, its gate, both reviews and the authority all pass. On a repository with a merge train, the pull request joins the train.

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What the agent cannot do, by design

Ankra keeps the decisions that grant power with people:
  • No agent can approve a pipeline’s authority. Approval grants secrets, credentials and network access, so it needs a person with pipelines.manage (ankra pipeline definitions approve). A pull request the agent writes that adds a secret runs without it until a person approves on the default branch.
  • No agent can merge around your rules. Merge when green waits for every condition, refuses forks, and is refused outright on a connection in Ask mode.
  • The token is the boundary. An mcp:read token cannot call a write tool at all. Give an agent mcp:write only where you want it to act.
  • Fork pull requests stay restricted whoever opened them: no secrets, no credentials, no shared caches.

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When the agent is Ankra’s own

You do not need a coding agent on your laptop to get this loop. Ankra’s own AI does it inside the platform:
  • In Ankra chat, ask it to watch a run. It wakes the conversation with the failing step, the log tail, findings and the gate verdict.
  • On a pull request, the AI review reads your pipeline’s result and findings, and a failed build gets a diagnosis in the pull request’s status comment.
  • From Slack or Teams, the AI Gateway answers questions about your runs and can investigate a failed build.