Automate Jira + PostgreSQL
The ticket system of record for engineering work. 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.
Meeting Follow-Through is a ready-made agent built around Jira; point its last step at PostgreSQL to finish this hand-off.
Automations teams run
Each of these runs with a reasoning step between the two tools, so what reaches PostgreSQL is a decision about the Jira event rather than a transcription of it.
When an issue is created or transitions in Jira…
…an agent can run parameterised queries in PostgreSQL — after reading the context and deciding it should.
When a sprint starts in Jira…
…an agent can write validated rows in PostgreSQL — after reading the context and deciding it should.
When a priority changes in Jira…
…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 create and update issues in Jira — with the reasoning recorded in the run’s receipt.
When a threshold is crossed in PostgreSQL…
…an agent can transition tickets with comments in Jira — with the reasoning recorded in the run’s receipt.
The Jira and PostgreSQL hand-off, setup template
Start with a custom-api call to {yoursite}.atlassian.net and a custom-api call to {host}:5432. Configure the Jira 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.
{
"id": "e38ef327-07c8-4d6a-a78a-b9c125623164",
"name": "Jira → PostgreSQL",
"nodes": [
{
"id": "8dbb276a-a5b2-4dcd-a054-2e6daa39faa2",
"text": "Run on a schedule",
"x": 512,
"y": 144,
"isEditing": false,
"type": "trigger-timer",
"icon": "connect",
"category": "trigger",
"isSelected": false,
"parameters": {
"fireOnStart": "No",
"scheduleType": "Interval",
"schedule": "Every 15 Minutes"
},
"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.",
"error": null,
"isActive": false,
"output": null,
"outputs": {}
},
{
"id": "125a2e48-ac81-4fee-a84a-7e3cbc595b30",
"text": "Review source and draft",
"x": 512,
"y": 336,
"isEditing": false,
"type": "agnt-agent",
"icon": "connect",
"category": "action",
"isSelected": false,
"parameters": {
"agentId": "CONFIGURE_AGENTID",
"message": "Read the Jira item. Decide whether it warrants action in PostgreSQL, and explain why.\nSource input: CONFIGURE_SOURCE_INPUT. Produce a reviewable draft only; do not take external actions."
},
"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.",
"error": null,
"isActive": false,
"output": null,
"outputs": {}
},
{
"id": "6510f5f9-f627-4a9b-aa13-1ab2fd20d97e",
"text": "Call PostgreSQL",
"x": 512,
"y": 528,
"isEditing": false,
"type": "custom-api",
"icon": "connect",
"category": "action",
"isSelected": false,
"parameters": {
"url": "postgresql://{user}:{password}@{host}:5432/{database}",
"method": "GET",
"authType": "None",
"query": "",
"headers": "{}"
},
"description": "Setup template for Custom API Request. This action node makes a custom API request to any endpoint with configurable method, headers, and authentication. Configure credentials, inputs and output mapping before use.",
"error": null,
"isActive": false,
"output": null,
"outputs": {}
}
],
"edges": [
{
"id": "90a025c4-8a50-4388-a298-711c5c48bb58",
"start": {
"id": "8dbb276a-a5b2-4dcd-a054-2e6daa39faa2",
"type": "output"
},
"end": {
"id": "125a2e48-ac81-4fee-a84a-7e3cbc595b30",
"type": "input"
},
"startX": 800,
"startY": 168,
"endX": 512,
"endY": 360
},
{
"id": "01d56db5-92b0-4aee-afe9-d5e1c60e98d0",
"start": {
"id": "125a2e48-ac81-4fee-a84a-7e3cbc595b30",
"type": "output"
},
"end": {
"id": "6510f5f9-f627-4a9b-aa13-1ab2fd20d97e",
"type": "input"
},
"startX": 800,
"startY": 360,
"endX": 512,
"endY": 552
}
],
"zoomLevel": 1,
"canvasOffsetX": 0,
"canvasOffsetY": 0,
"isTinyNodeMode": false
}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 Meeting Follow-Through
Meeting Follow-Through is a working agent built around Jira. 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
- Install AGNT — it runs on your own machine and needs no account to start.
- Authorise PostgreSQL (a local endpoint on your own machine) and Jira (one OAuth sign-in). Nothing is stored anywhere but your disk.
- Describe the job in plain language, or paste the definition above; custom-api does the reading and custom-api the writing.
- Gate anything you would not want done unattended, then let it run and read the first receipt end to end.
Jira and PostgreSQL — common questions
Can I connect Jira to PostgreSQL without writing code?
You can build it entirely from the canvas. Authorise Jira with one OAuth sign-in, PostgreSQL with a local endpoint on your own machine, then tell the agent what meeting actions become tickets automatically 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 Jira to PostgreSQL automation?
A field mapping copies values and breaks on the first record nobody anticipated. The middle step here reads the Jira item in full and decides — whether it matters, how to summarise it, and what belongs in PostgreSQL. Deciding to do nothing is a valid outcome, which no mapping can express.
Does my Jira and PostgreSQL data leave my machine?
AGNT Community Core is local-first, so there is no vendor middleman holding your Jira or PostgreSQL tokens. The runtime talks directly to both services. Choose a local model and the content of what it reads never leaves the machine at all.
What does a Jira and PostgreSQL run leave behind?
A receipt: what was read in Jira, which tools ran with which arguments, what the agent concluded, and what it wrote to PostgreSQL. Anything consequential can sit behind an approval gate so a person signs off before it happens.
