We connect Claude to the Jobber account you already run, through an MCP server built on the official API, the same API we ship paid Jobber integrations on today. Which clients haven't been invoiced. Which quotes went quiet. What this customer's history looks like. Asked in plain English, answered from live data. Read-only first, so it cannot break anything. You own the code.
Book a discovery callWhich clients haven't been invoiced. Which quotes went quiet. What we did for this customer last spring. The data sits in Jobber, and getting an answer means the owner or the office manager clicking through reports, because nobody else knows where to look.
The AI tools your team already pays for answer questions about the world, and know nothing about your shop. Pasting exports into a chat window works once, goes stale immediately, and puts customer data somewhere you don't control.
Subscription AI tools for the trades ask to connect to your account and start acting in it immediately. One bad guess writes into the system your whole shop runs on. That risk is why most owners never connect anything.
Shops are hiring for exactly this right now, and most of the offers they get are a subscription in front of somebody else's account. Here is the real map.
| The option | What it can answer | Can it act in Jobber | Who controls it |
|---|---|---|---|
| Jobber's own AI features | What Jobber's roadmap decided it should answer, inside the app. | Inside Jobber only, on Jobber's terms. | Jobber. Features change with your plan and their roadmap. |
| Zapier plus a GPT | Single records passed through a zap. No account-wide questions. | Simple one-way pushes. Fragile when a step changes. | You rent the middle. Each new question is a new zap. |
| A custom MCP server | Anything the API exposes: clients, jobs, quotes, invoices, visits, history. | Read-only first. Write actions only behind your approval list. | You. It's your code on your infrastructure, and you own it. |
Jobber's own AI features evolve with their roadmap and your plan. Check what your subscription currently includes. Last verified 2026-08-16.
The core build. Claude connects to your Jobber through a translator we build, and anyone you authorize asks questions in plain English: overdue invoices, quiet quotes, this customer's full history. It only reads.
Once the read-only layer has earned trust, we add the specific actions you approve, one by one: draft a quote, create a client, add a note. Every action logged, nothing outside the list.
"Revenue per crew last month, compared to the month before." Answered in seconds from live data, instead of a Friday of exports and SUMIFS. Pairs with our reporting builds when you want it on a schedule too.
Before a call or a site visit, one ask returns everything: every job, every quote, every invoice, every note, summarized. Your techs walk in knowing the property.
When an AI receptionist or intake form takes the call, the booking has to land in Jobber correctly: right client, right property, right visit. We build that landing so the front end can be whatever you choose.
Query budgets so the AI can't throttle your account, a permission list for who can ask what, and a log of every question and every action. Boring on purpose. This is the part that makes the rest safe.
Want the technical walkthrough first? We wrote uphow a Jobber MCP server actually works, including code. And when the goal is scheduled reports rather than conversational answers, that isour Jobber reporting service.
The reason most owners never connect AI to the system their shop runs on is simple: fear of a bad write. We build in the order that removes the fear. Stage one reads and recommends. It cannot create, edit, or delete anything.You use it for weeks, you see every answer sourced from your real data, and the worst possible outcome the whole time is a wrong answer you ignore.
Only then, if you want it, we add write actions from a list you approve: draft a quote, add a note, create a client. Each action logged with who asked and what changed. The approval list is yours to grow or freeze.
An AI layer stands or falls on how it treats the API underneath.Jobber's API has a strict query cost budget, and we know it from production: one of our KPI dashboard loads costs 13,456 to 20,762 points against a 10,000 point budget that refills at 500 points a second, which is why it is engineered as staged queries instead of one big pull. We publishedour measurements. An AI that queries carelessly throttles the account your office is using. Ours budget every tool call.
Subscription AI vendors can't show you numbers like that. We can, because we hit the walls on paid work first.
The production measurements above come from paid work, not a lab. A multi-location coatings contractor runs 22 people on Jobber, on five builds we shipped alongside it: crew boards, reporting, and the API plumbing an AI layer stands on.Every build after the first was requested by the client, which is the strongest review a system gets. The AI layer on this page is built with the same budget-every-query discipline that keeps that account fast.
Same build, different CRM. The MCP pattern works against any platform with a real API: read-only tools first, approved actions later, your code throughout. The overview of what we build on each platform is on ourintegrations page.
You tell us the five questions you wish you could just ask your Jobber account. Both founders are on the call, start to finish.
What we'd build, in what order, at a fixed price. The plan is yours to keep, free, whether we end up working together or not.
The first piece is always the read-only server, because it can't break anything and it proves the value fast. Write actions come later, one approval at a time.
No subscription for access to your own account. $0 per seat, at 5 people or at 50. If we disappeared tomorrow, your system keeps running.
Anonymized here. Ask on the call and Dan will tell you whose shop each one is.
"They just got how our business works."
"We needed our Jobber account connected to our internal system, and Danilo's team understood the workflow almost immediately. They handled the integration, cleaned up a few things we were struggling with, and made the whole process much easier for our team."
HVAC Company OwnerJobber CRM Integration
"We stopped doing a ton of this stuff manually."
"Our biggest problem was that our office team was constantly moving information between systems. Danilo's team built the integration for us and automated a big part of the workflow. It's one of those projects where you wonder why we didn't do it sooner."
Home Services Business OwnerCustom CRM & Workflow Automation
MCP, the Model Context Protocol, is an open standard that lets an AI assistant like Claude connect to outside systems through a defined set of tools. An MCP server for Jobber is a small piece of software that translates between the AI and Jobber's official GraphQL API. The AI asks in plain language, the server runs the real queries against your account, and the answer comes back grounded in your actual data.
Yes, through an MCP server built against Jobber's developer API. As of August 2026 Claude has no built-in Jobber connection, so the bridge has to be built. Once it exists, Claude can read your clients, jobs, quotes, invoices, and visits, and answer questions about them. That bridge is exactly what we build.
Safe is a design decision, and it is the center of how we build. Stage one is read-only: the AI can look and cannot touch, so the worst case the whole time is a wrong answer you ignore. Write actions come later, limited to a list you approve, each one logged. Your data flows through infrastructure you own.
Anything the API can see. Which invoices are overdue and by how much. Which quotes have sat a week without an answer. Everything we've done for this client since 2023, summarized. Revenue per crew this month. The questions your office answers today by exporting reports and cross-referencing tabs become questions you just ask.
No. Your team keeps the Jobber they already know. The AI layer sits alongside it, connected through the official API. Nothing about scheduling, quoting, or invoicing changes for the crew. The change is that the answers stop being locked behind one person's report-clicking.
Use it, it's already in your subscription. The difference is control and reach. Jobber's AI features run inside Jobber, answer what Jobber designed them to answer, and change when Jobber's roadmap changes. A custom MCP layer answers your questions, connects to the rest of your stack, and belongs to you. Many shops want both.
You get a fixed price in writing on day 7, before you commit to anything. You pay once and own the code, the server, and the roadmap. There is no per-seat fee and no monthly subscription to your own account. Ongoing hosting runs on infrastructure you control.
Yes. The shape is identical: an MCP server against the platform's API, read-only first, approved actions later. ServiceTitan and Housecall Pro gate their APIs differently. Only the translator changes; the safety model stays the same.
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Independent builders. Not affiliated with Jobber, Housecall Pro, ServiceTitan or Anthropic.
