Jd Intel MCP server

jd-intel

Stop pasting job descriptions into AI assistants. Let your AI fetch them directly.

Full text. Clean structure. Across seven major ATS. No copy-paste. No context loss.

Why this exists

Your AI assistant already knows a lot about you. Your resume is in its memory. Your target roles, your past projects, your background. Ready to help the moment you feed it a job description.

So you copy-paste.

A JD from one company. Another from the next. A half-dozen more from your target list. Half have broken HTML. Salary info dies in translation. Links get stripped. And for every role, the dance starts over.

You could wait for the job boards to ship their own MCPs. They'll get there eventually. On their timeline. Filtered through their priorities, not yours. Tied to their query abstractions.

jd-intel skips that wait. Raw JDs, fetched directly by your AI, on your terms. One level below the curated layer.

Try asking your AI:

"Find AI/ML engineering jobs posted this week."

"What product designer roles are open at fintechs right now?"

"Pull the staff PM roles posted in the last 7 days."

Done.

Why not just scrape?

Because scraping breaks where jd-intel doesn't:

• Full JDs when browsing fails. SPA-rendered boards, slow loads, auth walls, and geo-restrictions block a browser. They don't block a public API call.
• Structured data, not HTML soup. Salary, location type, department, and clean markdown, normalized across seven ATS.
• No keys, no browser. Public APIs only. Runs anywhere your AI does.
• One schema, every platform. Greenhouse, Lever, Ashby, SmartRecruiters, Teamtailor, Recruitee, Workday return the same shape.

What you can do with it

• Look up open roles at any company directly from your AI, no copy-paste
• Tailor your resume across ten roles in one conversation
• Rank openings by fit with your background
• Scan a whole sector: "Pull open roles at fintech companies posted this week"
• Research teams by reading their JDs in bulk

The toolkit fetches. Your AI thinks.

Install

Works with MCP-aware AI clients: Claude Desktop, Claude Code, Cursor, Windsurf, VS Code. ChatGPT, Gemini, and other non-MCP clients don't support this yet. They use different tool-calling systems. (We wish they did. The protocol works the same way regardless of which AI you talk to.)

Everything runs locally on your machine. That also means desktop only: mobile apps can't run a local MCP server, so jd-intel isn't available on phones or tablets.

Claude Desktop (one-file install, no terminal)

The simplest path. No Node.js, no terminal: Claude Desktop runs the server on its own bundled runtime.

1. Download the extension: jd-intel.mcpb.
2. In Claude Desktop, open Settings, then Extensions, then Advanced settings, and click Install Extension. Pick the file you downloaded.
3. Review the access summary, click Install, then start a new chat. The tools appear automatically.

Shortcuts: drag the .mcpb onto the Settings window, or double-click it when your system opens .mcpb files with Claude Desktop. The extension is open source and unsigned, so Claude Desktop shows an "unverified" notice. Choose Install Anyway.

Shortened. The full README is on GitHub.