Hiring used to mean toggling between browser tabs, copying job descriptions into form fields, and clicking through multi-step wizards on every job board. AI changes that. You can now describe a role in plain English and have an AI assistant structure, validate, and submit the posting for you, in a single conversation.
This guide walks through two main ways to post remote jobs using AI, from the simplest (no account needed) to the most powerful (full employer dashboard through conversation).
The simplest path: post a job in one message
If you don't have a Himalayas account and just want to get a role live quickly, the post_job_public MCP tool handles everything. Connect the Himalayas MCP server to any compatible AI assistant — Claude Desktop, Cursor, Windsurf, VS Code, or Zed — and say something like:
"Post a remote Senior Backend Engineer role. Company: Acme Corp, website acme.io, contact hiring@acme.io. Full-time, $150-180K, requires Go and PostgreSQL experience."
The AI structures the posting, the MCP returns a Stripe checkout link for payment, and after checkout the job is posted on Himalayas. Your email domain needs to match your company URL, that's the only verification required.
This is ideal for one-off postings when you don't need ongoing job management or analytics.
The power workflow: employer account + MCP
Creating a free Himalayas employer account unlocks the full suite of employer MCP tools. Jobs are free to post. You get view counts, click metrics, editing, screening questions, and paid promotion options, all through natural conversation.
The setup takes under two minutes.
- Sign up to Himalayas and follow the onboarding steps.
- Add this to your AI assistant's MCP configuration:
{
"mcpServers": {
"himalayas": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://mcp.himalayas.app/mcp"]
}
}
}
On first use, you'll authenticate through a secure login flow. After that, posting is as natural as talking:
"Post a remote Product Designer role, full-time, $120-150K. We need someone with 3+ years of Figma experience and a portfolio. Add a screening question asking candidates to describe their design process for a recent B2B SaaS feature."
The AI handles field mapping, description formatting, screening question structuring, and submission. You can also ask it to list your active postings, check performance metrics, update salary ranges, or delete expired roles, without ever opening a dashboard.
Want to find talent that match your role? Just ask it. Search candidates, pull up their full profiles, and message them directly, all in the same conversation. See How to Hire Remote Talent with AI for the full recruiting workflow, or Free Alternative to LinkedIn Recruiter for how it compares to LinkedIn.
Let AI write your job description
One of the biggest advantages of posting through AI isn't just the submission step, it's the writing. A good AI assistant will draft a complete job description from a brief prompt, and you can iterate on it conversationally before posting.
Try something like:
"Write a job description for a remote Staff Data Engineer. We're a Series B fintech startup, 80 people, building real-time fraud detection. The role needs Spark, Kafka, and dbt experience. We offer competitive equity, async-first culture, and unlimited PTO. Make the tone direct and engineering-focused. No fluff."
The AI drafts a full description with responsibilities, requirements, nice-to-haves, benefits, and company context. You refine it in conversation ("make the requirements section shorter", "add a note about on-call expectations") and then post directly.
This works with any AI assistant connected to the Himalayas MCP, and it works equally well with ChatGPT, Gemini, or other models if you're drafting descriptions separately and posting through the MCP afterward.
Screening questions through conversation
Screening questions filter unqualified applicants before they hit your inbox. Describing them in natural language is far faster than navigating form builders:
"Add three screening questions: ask if they have production Kubernetes experience (yes/no), ask them to describe a data pipeline they've built end-to-end (text), and ask about their preferred start date with options: immediately, 2 weeks, 1 month, or flexible."
The MCP supports boolean (yes/no), free-text, and multiple-choice question types. The AI structures them correctly from your description.
Promoting your posting
Free postings get standard visibility. Two optional paid extras increase reach:
Sticky placement ($199) pins your job to the top of relevant search results. Newsletter feature ($99) includes it in the weekly email to Himalayas subscribers. Tell your AI assistant "add sticky placement to the Staff Data Engineer posting" and it returns a Stripe checkout link. Add your payment details in Stripe, and the job will be posted automatically.
What about ChatGPT, Gemini, and other AI assistants?
MCP is an open standard, it's not exclusive to any one AI provider. Any assistant that supports MCP can connect to the Himalayas server. As of early 2026, Claude Desktop (and Claude Code and Claude Cowork), ChatGPT, Cursor, Windsurf, VS Code, and Zed all have native MCP support. OpenAI and Google are also building MCP support into their platforms.
Even without MCP support, you can use any AI to draft job descriptions and then post them through an MCP-connected tool, or use the Himalayas web interface directly.
Getting started
The fastest path from zero to posted:
- Connect the Himalayas MCP server to your AI assistant (2 minutes)
- Create a free employer account at himalayas.app if you want ongoing management
- Describe the role you're hiring for in natural language
- Review the AI's structured posting and confirm
- The job goes into review and is typically live within hours
Jobs are free to post. The MCP server goes well beyond job posting - you also get salary benchmarking, company profile management, and talent search, and direct candidate messaging. All for free. See the full MCP documentation for everything available.
