Automate HubSpot + PostgreSQL
The CRM your pipeline reporting depends on. 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.
Lead Researcher is a ready-made agent built around HubSpot; point its last step at PostgreSQL to finish this hand-off.
Automations teams run
These are not field mappings. An agent reads the HubSpot side, works out what it means, and only then decides what — if anything — should happen in PostgreSQL.
When a contact or deal is created in HubSpot…
…an agent can run parameterised queries in PostgreSQL — after reading the context and deciding it should.
When a stage changes in HubSpot…
…an agent can write validated rows in PostgreSQL — after reading the context and deciding it should.
When a form submits in HubSpot…
…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 enrich contacts in HubSpot — with the reasoning recorded in the run’s receipt.
When a threshold is crossed in PostgreSQL…
…an agent can update deals and notes in HubSpot — with the reasoning recorded in the run’s receipt.
HubSpot to PostgreSQL, setup template
Start with a custom-api call to api.hubapi.com and a custom-api call to {host}:5432. Configure the HubSpot 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": "5782f44f-2537-4921-a2ab-b1066612ccce",
"name": "HubSpot → PostgreSQL",
"nodes": [
{
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"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": "33ce8592-1ded-48a7-aa19-d0ad0cb4e7fe",
"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 HubSpot 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": "a92a5a48-bbec-4e76-ad02-72c25308221c",
"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": "bcefa480-43d3-472f-a97c-599b70e82072",
"start": {
"id": "c6adfcdb-8867-43ec-a261-9ad9e467abc4",
"type": "output"
},
"end": {
"id": "33ce8592-1ded-48a7-aa19-d0ad0cb4e7fe",
"type": "input"
},
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},
{
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"id": "33ce8592-1ded-48a7-aa19-d0ad0cb4e7fe",
"type": "output"
},
"end": {
"id": "a92a5a48-bbec-4e76-ad02-72c25308221c",
"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 Lead Researcher
Lead Researcher is a working agent built around HubSpot. 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
Wiring HubSpot to PostgreSQL
- Download AGNT Community Core — free and local-first.
- Connect HubSpot with one OAuth sign-in and PostgreSQL with a local endpoint on your own machine; both land in the local vault.
- Start from a marketplace workflow, or drop a custom-api node and a custom-api node onto the canvas with an agent between them.
- Put an approval gate on anything consequential, then run it — the receipt shows what was read in HubSpot and what was written to PostgreSQL.
HubSpot and PostgreSQL — common questions
Can I connect HubSpot to PostgreSQL without writing code?
No code is required. Add both connections in the vault (HubSpot uses one OAuth sign-in, PostgreSQL uses a local endpoint on your own machine), then either install a marketplace workflow for this pair or drag the two nodes onto the canvas and put an agent between them.
How is this different from a field-mapping HubSpot 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 HubSpot, classify it against criteria you wrote in prose, draft something new, and act only when it is warranted.
Does my HubSpot 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 HubSpot, PostgreSQL and whichever model you chose — and pointing that at Ollama or LM Studio keeps everything on your hardware.
What does a HubSpot and PostgreSQL run leave behind?
Every run is recorded end to end — the HubSpot items examined, the decision and its reasoning, the resulting PostgreSQL write. That record is what makes it reasonable to let this run unattended, and what lets you widen its remit on evidence.
