Automate GitHub + PostgreSQL
Where the code — and half the process — lives. The production database your reports should come from. Put an agent between them and the hand-off stops being manual: it reads, decides, acts, and shows its work.
First-Pass Reviewer is a ready-made agent built around GitHub; point its last step at PostgreSQL to finish this hand-off.
Automations teams run
Unlike field-mapping automation, the step in the middle is an agent: it can summarise, classify, judge and draft, not merely copy values from GitHub into PostgreSQL.
When a PR opens or merges in GitHub…
…an agent can run parameterised queries in PostgreSQL — after reading the context and deciding it should.
When an issue is filed in GitHub…
…an agent can write validated rows in PostgreSQL — after reading the context and deciding it should.
When a release is cut in GitHub…
…an agent can produce report extracts in PostgreSQL — after reading the context and deciding it should.
When a scheduled query runs in PostgreSQL…
…an agent can comment on PRs and issues in GitHub — with the reasoning recorded in the run’s receipt.
When a threshold is crossed in PostgreSQL…
…an agent can open issues with structured detail in GitHub — with the reasoning recorded in the run’s receipt.
Copy this GitHub → PostgreSQL workflow
Start with the github-api node and a custom-api call to {host}:5432. Configure the GitHub source payload, the agent input, and the PostgreSQL operation. The sequential template does not implement conditional writes or approval by itself.
This is a schema-checked starting point, not an end-to-end tested automation. Replace every CONFIGURE_ value, choose the operations you intend, connect credentials and map source outputs into later inputs. An edge orders steps; it does not supply a condition, an approval gate or a field mapping. Add and test those controls explicitly before any write. Cloud APIs and model providers may receive data. Keep the workflow inactive until tested with fixtures.
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"schedule": "Every 15 Minutes"
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"description": "Setup template for Timer Trigger. This trigger node fires the workflow at specified intervals or at a specific time. Configure credentials, inputs and output mapping before use.",
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"isSelected": false,
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"description": "Setup template for Agent Chat. Chat with an AI agent from your agent library. Select an agent and send messages to interact with it within your workflow. Configure credentials, inputs and output mapping before use.",
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"method": "GET",
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"headers": "{}"
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}Configure GitHub API
Interact with GitHub: repos, branches, files, issues, comments, pull requests, reviews, releases, Actions/CI, and search.
- action — The action to perform on GitHub Current example:
GET_AUTHENTICATED_USER. - owner — The owner of the repository (not needed for account-level or search actions) Current example:
CONFIGURE_OWNER. - repo — The name of the repository (for CREATE_REPO: the name of the new repository) Current example:
CONFIGURE_REPO.
Configure Custom API Request
This action node makes a custom API request to any endpoint with configurable method, headers, and authentication.
- url — The URL of the API endpoint Current example:
postgresql://{user}:{password}@{host}:5432/{database}. - method — The HTTP method for the request Current example:
GET. - authType — The type of authentication Current example:
None. - query — Query parameters for the request (e.g., 'key1=value1&key2=value2') Current example:
. - headers — Optional headers for the request. e.g., {"Content-Type": "application/json"} Current example:
{}.
Install First-Pass Reviewer
First-Pass Reviewer is a working agent built around GitHub. Install it, point its last step at PostgreSQL, and you have this hand-off without building it from an empty canvas.
Runs on your own machine · See what it does
Build it in AGNT
- Get AGNT Community Core. Free, local, no sign-up needed to run a workflow.
- Add both connections to the vault — GitHub takes one OAuth sign-in, PostgreSQL takes a local endpoint on your own machine.
- Configure the nodes above, or start from a marketplace workflow and edit it. The agent in the middle is the part worth spending time on.
- Run it once with an approval gate in place. The receipt tells you what it read, what it concluded, and what it changed in PostgreSQL.
GitHub and PostgreSQL — common questions
Can I connect GitHub to PostgreSQL without writing code?
You can build it entirely from the canvas. Authorise GitHub with one OAuth sign-in, PostgreSQL with a local endpoint on your own machine, then tell the agent what first-pass review on every diff should look like once PostgreSQL is involved. Code is an option for the unusual cases, never a requirement for the common ones.
How is this different from a field-mapping GitHub to PostgreSQL automation?
Mapping tools move data; this reasons about it. Rather than copying a field into PostgreSQL, the agent can weigh what arrived from GitHub, classify it against criteria you wrote in prose, draft something new, and act only when it is warranted.
Does my GitHub and PostgreSQL data leave my machine?
Not to us. AGNT runs locally and both sets of credentials are encrypted on your own disk. Outbound traffic goes only to GitHub, PostgreSQL and whichever model you chose — and pointing that at Ollama or LM Studio keeps everything on your hardware.
What does a GitHub and PostgreSQL run leave behind?
You get an auditable trail rather than a success flag. It shows the GitHub context the agent worked from, the judgment it made about metrics pulled straight from source, and the exact change applied in PostgreSQL, with approvals attached where you required them.
