CHATBOTS

Conversational GitHub Repo Access Provisioner

A Teams chatbot that takes a repo-access request, routes it to the repo owner for approval, and on approval adds the user to the GitHub team at the right permission level.

CategoryChatbots
Enginesim
Difficultyintermediate
Triggerchat
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDeveloper requests repo access in TeamsMicrosoft Teams
  • ActionSend approve/deny prompt to repo ownerMicrosoft Teams
  • LogicGate: continue only if owner approves
  • ActionAdd user to GitHub team at requested permissionGitHubGitHub
  • ActionLog grant and approver to audit tableAirtableAirtable
  • OutputConfirm grant to requester in TeamsMicrosoft Teams

What it does

Developers ask the IT bot for access to a GitHub repository in plain language. The bot identifies the repo and the permission level requested, asks the repo's code owner to approve or deny inline, and — only after approval — adds the requester to the matching GitHub team. No more open-ended Slack threads or forgotten access requests.

When to use it

Use this when repo access is granted ad hoc and you need a fast but governed path: self-serve request, owner approval, automatic provisioning, and a record of who approved what.

How it works

  1. 1A developer messages the bot in Teams asking for access to a repo ("need write on payments-api").
  2. 2The bot parses the repo name and requested permission (read/write/admin).
  3. 3It posts an approve/deny prompt to the repo's designated owner in Teams.
  4. 4Logic gate: proceed only on explicit approval; otherwise notify the requester it was declined.
  5. 5On approval, it adds the user to the appropriate GitHub team via the API.
  6. 6The bot confirms back to the requester and logs the grant for audit.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect Microsoft TeamsChannels, chats, files.
  2. 2
    Connect GitHubRepos, issues, pull requests, actions.
  3. 3
    Connect AirtableBases, tables, views, automations.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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