We've all been there. It's the end of the quarter, and you need to pull together a performance report. Your revenue data lives in one spreadsheet. User metrics sit in another. Product updates are scattered across Google Drive. Strategic notes hide in Notion. You start tabbing between windows, copying numbers, and manually assembling everything into a document.

It takes hours. And by the time you're done, you're wondering if there's a better way.

There is. We recently connected our Tinq AI workspace to Cursor through the Model Context Protocol (MCP), and watched our AI-powered code editor assemble a comprehensive quarterly report in minutes, complete with data visualizations and strategic recommendations, all without leaving the terminal.

What We're Solving: The Context Problem

Most AI tools are context-blind. They don't know where your data lives or how your business actually works. You end up feeding them information manually, one query at a time, losing the thread as you switch between tools.

Tinq AI addresses this by connecting all your knowledge sources into one secure, searchable workspace. Google Drive, Notion, SharePoint, Salesforce, and more all get indexed and unified. When you ask a question, the system knows where to look.

But we wanted to go further. We wanted our development environment itself to understand our business context.

Enter MCP: A Simple Bridge Between Tools

The Model Context Protocol is an open standard that lets AI applications share context with each other. Think of it as a conversation format that different tools can understand.

When Cursor connects to Tinq AI through MCP, it gains immediate access to your entire workspace. Documents, spreadsheets, notes, all of it becomes queryable from within your code editor. No more context switching. No more manual uploads.

Setting Up the Connection

Getting started took about five minutes. We added the Tinq MCP Server to Cursor's configuration with our API key. No infrastructure to manage, no complex setup.

Once connected, we could see our data sources right in the Cursor interface. We had already connected Google Drive to our Tinq workspace, where our quarterly spreadsheets and performance documents lived. The MCP connection meant Cursor could now search and retrieve that information on demand.

Building a Quarterly Report in Real Time

We gave Cursor a straightforward instruction: "Generate a Q4 performance report using our quarterly data. Include user growth, revenue trends, and expense analysis. Create visualizations and provide strategic recommendations."

Cursor queried our Tinq workspace through MCP, pulling the relevant spreadsheets from Google Drive. We watched it parse user metrics, revenue figures, and expense data. Then it started assembling.

Within minutes, we had an HTML report with working Chart.js visualizations. User growth appeared in a line graph. Revenue and expenses showed up as a bar chart comparing quarters. The report included calculated metrics like growth rates and margins, all derived from our actual data.

The strategic recommendations surprised us. Because Cursor had access to our full workspace context, it could reference past strategic notes and align its suggestions with our stated goals. It wasn't just generating generic business advice. It was responding to our specific situation.

What Makes This Different

The key difference is persistence and context. Traditional workflows require you to manually provide context every time. With Tinq AI connected via MCP, that context is always available. Your AI tools can reference the same knowledge base you do.

When we needed to update the report with revised numbers, we just asked. Cursor pulled the new data from our workspace and regenerated the visualizations. No re-uploading. No re-explaining what we needed.

The security model matters too. Tinq respects source-level permissions and access controls. If certain team members can't access a document in Google Drive, they can't query it through MCP either. Your data governance stays intact.

The Practical Benefits

Let's be concrete about what this saves. Before, assembling a quarterly report meant opening spreadsheets, copying data, creating charts in a separate tool, drafting analysis in a document editor, and then combining everything. Easily two to three hours of work.

With Tinq AI connected to Cursor via MCP, the same report took about five minutes to generate and another five to review and refine. That's not just efficiency. It's the difference between spending your afternoon on data entry versus strategic thinking.

The workflow extends beyond reports. Need to write code that references your API documentation? Cursor can pull it from your workspace. Building an internal dashboard? Your metrics and KPIs are already accessible. Drafting a proposal that needs supporting data? It's there.

A Smoother Way to Work

We're not saying this replaces human judgment or strategic thinking. What it replaces is the tedious work of gathering, formatting, and synthesizing information that you already have.

The connection between Tinq AI and Cursor through MCP represents something simple but meaningful: AI tools that actually understand your business because they can access the same context you do. Your documents work for you. Your data becomes immediately useful. Your tools talk to each other.

If you're spending hours each week pulling together information from scattered sources, this is worth exploring. Connect your workspace once, and every AI tool you use gets smarter.

We'd love to hear how you're connecting your data and tools. What workflows are you looking to simplify next?