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jobctl
The job application tracker your AI agent keeps updated
jobctl is a job application tracker built MCP-first: AI agents (Claude, ChatGPT, Cursor) are the primary users - they record applications, interviews, salaries and next actions while you talk to them. You review everything in a clean dashboard: pipeline board, analytics, interview timeline, CV attachments. Remote MCP server with OAuth 2.1, listed in the official MCP Registry. Free.
Hi Product Hunt! 👋
Three weeks ago I lost my job - the client's budget got cut three days before my probation ended. I started job hunting the modern way: with AI agents doing the heavy lifting. But every tracker I tried was built for humans clicking forms, while my actual workflow was "Claude, I applied to Bosch as Tech Lead, prio A, follow up Friday."
So I built jobctl - a tracker where the agent is the first-class user. It speaks MCP (remote server, OAuth 2.1, official MCP Registry), so any agent can add applications from a single sentence, log interviews with attendees and prep links, attach tailored CVs it just generated, and answer "what's burning today?" I read the dashboard; the agents do the bookkeeping.
The meta part: jobctl was also built by the same agentic workflow it serves - spec-first development, deterministic quality gates, AI agents writing the code. And it's not a demo: I'm running my own active job search through it right now - every application, interview and follow-up in my tracker was entered by an agent while I focused on the actual interviews.
It's free while I figure out where this goes. I'd love your feedback - especially from fellow MCP builders: tool design, OAuth flow, what you'd want your agent to track next.
Day 2 update from the maker - and a question I genuinely want your take on.
First: thank you for the warm welcome, the comments and the first users - watching real MCP connections appear in the logs never gets old.
The question: where should an AI agent's autonomy END in a tool like this? Adding an application from "I applied to Bosch, prio A, follow up Friday" is clearly fine. Deleting data is clearly not. But the middle is interesting: should an agent be allowed to mark an application as rejected on its own? Update your salary expectation? Draft a follow-up email? In jobctl the deterministic core validates every write and everything lands in an audit feed - but the permission line itself is a design choice, and I want to draw it where users actually want it. Tell me where you would draw it.
About jobctl on Product Hunt
“The job application tracker your AI agent keeps updated”
jobctl was submitted on Product Hunt and earned 8 upvotes and 2 comments, placing #133 on the daily leaderboard. jobctl is a job application tracker built MCP-first: AI agents (Claude, ChatGPT, Cursor) are the primary users - they record applications, interviews, salaries and next actions while you talk to them. You review everything in a clean dashboard: pipeline board, analytics, interview timeline, CV attachments. Remote MCP server with OAuth 2.1, listed in the official MCP Registry. Free.
jobctl was featured in Productivity (658.2k followers), Artificial Intelligence (475.9k followers) and Career (2.2k followers) on Product Hunt. Together, these topics include over 272.6k products, making this a competitive space to launch in.
Who hunted jobctl?
jobctl was hunted by Dmytro Rybka. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Dmytro Rybka