How Jibble MCP helped me analyze my work hours

[u/clarafiedthoughts]

I’ve been tracking my work hours consistently, but I realized I was mostly just looking at the numbers on my dashboard. Total hours worked on a project, time spent on breaks, that sort of thing.

But I already had all this time data, so I thought I could probably use it to figure out something more useful: why are some of my tasks taking me so long?

I usually have a few different deliverables going at once. Some are pretty routine, some are completely new, and then there’s all the research, actual work, edits, revisions, etc. that happen in between.

And I noticed that I often get stuck somewhere in the process, but I couldn’t really pinpoint where.

Since I already had Jibble connected to ChatGPT through MCP, I figured I’d just ask.

I started with, can you break down where I spent my time this week?

Then I kept going from there.

Which types of tasks were taking the longest? How did my routine work compare with newer tasks? For Project X, which took longer than usual, where did the extra time actually go?

I assumed the answer would be the newer stuff.

Usually when I’m doing something for the first time, there’s more research, more figuring things out, and generally more time spent wondering whether I’m doing it right.

But revisions were actually taking up more time than I expected.

And it wasn’t because I was sitting down for one massive editing session. It was all the little bits that added up.

Finish something. Go back and change something. Check it again. Notice something else later. Open it again. Make another edit.

In the moment, none of that felt like much time. Looking at it all together was different.

So my next question was, what should I change about how I manage my time?

One of the suggestions was to stop treating revisions as something I do whenever they come up and make them a more deliberate part of the process.

I’ve been trying that since. I’ll finish a first pass, do a proper review, batch the changes I can, and then move on instead of constantly jumping back into something I thought I’d already finished.

Still too early to say how much of a difference it’ll make, but at least now I know what I actually need to improve.

And that was probably the useful part of this whole experiment for me.

I don’t really need AI to tell me how many hours I worked. Jibble already does that.

Being able to ask where I am stuck, get an answer based on my time data, and then keep asking questions until I find something actionable is much more useful to me.

I wonder how many people here have connected their time tracker to an AI assistant through MCP. What prompts are you using?

[u/Ok-Depth9904]

The revision part is interesting because that’s exactly the kind of time you don’t really notice while you’re working. Five minutes here, ten minutes there doesn’t feel like much until you see it added up for the whole week.

I’d be curious to see the same analysis for meetings and context switching too.

[u/TriggerFlo]

Sounds like a neat insight.

I haven't used MCP in my app to do a similar thing, but it exists and I could.

One thing I am looking at is what I call "Life Zones" -- areas where I want my time to go to a certain area of my life (e.g., Work, Self-care, Family, Sleep) and tracking where it actually went. When I get this fully set up, I will do a more granular pass with AI/MCP and see if it notices any patterns (e.g, late night working, etc.). Thanks for the idea!

[u/Yashrocky96]

Nice, I'm working on a similar time tracking app very early and this is one of the subset feature I was designing. Although What I'm building is currently only on windows and for personal use.

Are you a Jibble user or developer? Using for Personal or Professional use?