Your project data, ready for the AI assistant you already use.
The Visibuild MCP is a secure connection between Visibuild and the AI assistant of your choice – Claude, Copilot, Gemini, ChatGPT, or any other tool that supports the Model Context Protocol. Once it’s switched on for your company, your team can ask questions of their project data in natural language without leaving the assistant they already use.
Who this article is for:
📖 Anyone on your team – read on to understand what the MCP can do, what you can ask, and when it’s the right tool.
🔐 Auth Managers – see Enabling MCP for your company below to switch MCP on for your organisation.
🔌 Ready to connect your AI? – once MCP is enabled for your company, see How to connect your AI assistant to Visibuild for step-by-step instructions for Claude, ChatGPT, Copilot, and more.
What the MCP unlocks
Three things that weren’t possible before:
Ask questions in plain English. “What’s the health of the Capital Towers project?” or “Show me defects mentioning waterproofing across all our active sites.” The assistant pulls the answer from Visibuild and explains it back to you.
Find issues by meaning, not exact wording. The same defect logged as “water ingress”, “leak around window head”, “damp staining bedroom 2” and “moisture under sill” surfaces as one signal. The MCP uses semantic search, so the assistant catches variants that keyword search misses.
Bring Visibuild into your AI workflows. If your team already uses AI assistants to summarise project status, draft reports, or analyse trends, the data they need can now come straight from Visibuild – no copy-paste, no exporting CSVs into a chat window.
What you can do today
These capabilities are live now:
Capability | What it means for your team |
List projects | Pull a list of every project your account has access to, so the assistant knows what portfolio it’s working with. |
List project locations | See the location structure of any project – useful for queries scoped to a specific level, zone, or unit. |
Project health overview | A single-call snapshot of visi totals by type, defects, tickets, and recent activity for a project. Scope it to one level, zone, or unit to ask “how’s Level 3 going?” as easily as “how’s this site going?” |
Semantic search across visis | Search defects, NCRs, inspections, tasks, hold and witness points by intent. Find groups of related issues in one call, across years and sites. |
Semantic search across tickets | The same intent-based search applied to tickets, so issue trends and recurring themes surface even when titles vary. |
Semantic search across project templates | Find templates used across your projects and see how they relate to the work recorded against them, including issues. |
List visis on a project | Page through the complete list of visis on a project – filtered by type, status, location, or assigned company – with exact counts. Use it when you need the full picture, not just the best matches. |
List tickets | Page through every ticket across your projects (including tickets not linked to a project), filtered by status, project, or location. |
List companies | See the head contractor and subcontractors across your projects – their trade disciplines, which projects they’re on, and how their assigned visis are tracking (open, closed, NA). |
Fetch a single visi | Once a relevant defect or inspection is found, the assistant can open it in full – title, status, location, description, and who it’s assigned to (including their company). |
Fetch a single ticket | Same as above for tickets – the full record on demand for the assistant to reason over. |
Fetch a single project template | Open a specific template in full to understand how it relates to the work being completed on a project. |
Search, list, and count work together. Semantic search returns the most relevant matches (up to 100), so it’s the right tool for “find issues like X”. The list tools page through the complete record set with exact totals, so they’re the right tool for “show me everything”. The project health overview gives you the counts both should reconcile with.
Example prompts
Spot recurring issues and improve your templates:
What are my common defects in Visibuild per project and how could we improve our templates to rectify them?
Keep an eye on how your subcontractors are tracking:
Which subcontractor has the most open defects across our projects, and is their close-out rate improving?
Drill into one part of a project:
How is Level 3 tracking on Capital Towers compared with the project overall?
Enabling MCP for your company (Auth Managers only)
Only users with the Auth Manager role can enable MCP for a company. MCP is off by default – once you turn it on, all members of your company will be able to connect their own AI assistant using your region’s MCP URL.
To enable it, go to your company settings in Visibuild and toggle MCP on:
Visibuild is hosted in regional environments, and each region has its own MCP URL. Once MCP is toggled on, share the URL for the region where your Visibuild data is hosted with your team:
Region | MCP URL to share with your team |
Asia-Pacific | |
Europe | |
North America |
Not sure which region you’re on? Check your Visibuild web address – the subdomain (apac, eu, or us) tells you which region hosts your data.
Once your team has the URL, point them to How to connect your AI assistant to Visibuild for step-by-step instructions on connecting Claude, ChatGPT, Copilot, and more.
Adding it to your AI assistant
The exact steps vary by assistant, but the shape is the same in all of them:
Open your assistant’s settings and find the Connectors, Integrations, or MCP servers section.
Add a new MCP server. Give it a name like Visibuild and paste in your region’s MCP URL.
Authorise the connection – you’ll be sent to Visibuild to sign in, and access will follow your existing permissions.
Start a new conversation in your assistant and try a question like “What projects do I have access to in Visibuild?” to confirm it’s working.
Once connected, the assistant will ask for your permission the first time it uses each Visibuild tool. You’re always in control of when it runs.
For detailed steps for your specific AI tool, see How to connect your AI assistant to Visibuild.
What makes the Visibuild MCP different
Plenty of platforms now expose their data to AI assistants. Most do it the simple way: wrap every database endpoint as a separate tool and let the AI figure it out. We’ve taken a different approach. Each Visibuild MCP tool is designed around a question your team actually asks, not around a database table.
In practice, that means:
Semantic, not keyword. Searches understand meaning, so the same defect logged five different ways across five teams finally shows up as one trend.
Portfolio-wide reach. Questions like “have we seen this before?” can run across your whole portfolio, not project by project.
Answers, not data dumps. Each tool is shaped to return a meaningful result in one or two calls, so the assistant spends its time explaining and acting on the answer rather than stitching it together.
Fewer turns, lower cost, less drift. Because the tools are tightly scoped, conversations stay focused and predictable.
A worked example
To show what this looks like in practice, here’s a conversation a QA manager might have with their assistant once the MCP is connected:
You: “Look across waterproofing defects on the last 18 months of projects and tell me what the recurring failure modes are.”
Assistant: Returns a clustered answer in one or two calls – grouped by location and root cause, drawing on issues logged with different wording across different teams.
You: “Based on that, what should we be checking earlier in the next project?”
Assistant: Uses the patterns from your real field data to suggest checks targeted at the failures your portfolio keeps hitting.
On a keyword-based interface, the first question alone would take many narrow searches – and would still miss the wording variants. The MCP gets you to the answer in a single conversation.
When the MCP is the right tool – and when it isn’t
Visibuild gives you three ways to get data out of the platform. Each is good at different things. Picking the right one keeps expectations realistic.
Use case | MCP | API | CSV export |
Ask questions of your project data in natural language | ✅ Best | – | – |
Pull project context into an AI workflow (Claude, ChatGPT, etc.) | ✅ Best | ⚠️ Works, heavier lift | – |
Search by meaning across visis and tickets | ✅ Best | ⚠️ Keyword only | – |
Self-serve for non-technical users | ✅ Best | – | ✅ Good |
Bulk data extraction (every defect, every field) | – | ✅ Best | ✅ Good for one-off |
Integrations with Power BI, data warehouses, BI tools | – | ✅ Best | ⚠️ Manual / scheduled |
Static reporting and offline analysis | – | ⚠️ Possible but overkill | ✅ Best |
Real-time / event-driven workflows | – | ✅ Best (webhooks) | – |
Auditable, repeatable queries with exact results | ⚠️ AI layer varies (list tools are exact) | ✅ Best | ✅ Best |
✅ Good for
Asking questions in natural language – “what’s the health of Capital Towers?”, “which defects in this project mention waterproofing?”
Pulling project context into AI workflows your team already runs
Surfacing patterns in unstructured text – semantic search beats keyword on visi titles and descriptions
Lightweight self-serve once connected – no engineering work needed on your side
❌ Not the right tool for
Bulk data extraction – the list tools can page through complete record sets, but they return summaries, not every field and attachment. For full exports, use the API or a CSV export.
Deterministic reporting where the same query must return identical results every time. The AI layer interprets queries, so framings can vary slightly. Use the API for anything that needs to be exact.
Integrations into other systems – Power BI dashboards, data warehouse syncs, third-party tooling all belong to the API.
Real-time or event-driven workflows – the MCP is pull-based and on-demand. Use API webhooks for triggers.
Compliance and audit trails – if you need a defensible, repeatable export, use CSV or the API, not an AI-mediated query.
Data, privacy and access
The MCP is a new surface for your data, so we want to be precise about how it works.
Off by default. The MCP is not enabled for any company until an Auth Manager switches it on in company settings. You won’t stumble into it – enabling it is a deliberate decision.
Your data stays in your region. The MCP runs in the same regional environment that hosts your Visibuild data – connecting an AI assistant doesn’t move your data between regions.
You stay in control of your data. The MCP is a read interface into the same data you already own in Visibuild. It doesn’t change ownership, sharing, or what’s stored.
Existing Visibuild permissions still apply. Whoever connects the MCP only sees what their Visibuild account can already see. It is not a bypass for project access or roles.
Agents don’t run tools without permission. Your team accepts each request to run a Visibuild tool in their AI interface. Every use is a conscious, opt-in action.
Your choice of assistant, your assistant’s terms. The AI assistant your team connects (Claude, ChatGPT, or another) is your decision, and that provider’s privacy terms govern anything they ask it.
For full details on how Visibuild handles your data, see our Trust Centre.
Getting started
If you’d like to explore using the MCP with your projects, talk to your Visibuild account contact. We’ll walk through what’s possible and help you get the most out of it.
And if there are capabilities you’d like the MCP to support, let us know – customer requests shape the roadmap, and we prioritise the tools that unlock the most value.