AI Dev Jobs MCP

AI Dev Jobs MCP

Selective Reading Rule

Start with:

• references/senior-master-standard.md
• references/usage-routing.md
• references/quality-checklist.md

Then load only the inherited docs, scripts, assets, or examples that match the user's actual task.

Overview

AI Dev Jobs is a remote MCP server that gives AI agents access to a live index of AI and ML job listings. As of April 17, 2026, the live MCP stats report 8,405 active roles across 489 companies, a $213,500 median salary, and 600 new jobs this week. Agents can search jobs by role, location, or company, retrieve full job details, list hiring companies, match roles to a profile, and get salary or aggregate market statistics. It is designed for AI agents that assist with job searching, recruiting, or labor market analysis.

When to Use This Skill

• Use when helping a user search for AI or ML engineering jobs
• Use when an agent needs to look up which companies are hiring for specific AI roles
• Use when building recruiting or talent-matching workflows
• Use when analyzing the AI job market (open positions, top companies, role distribution)

MCP Configuration

Add the AI Dev Jobs MCP server to your client configuration. The endpoint uses streamable HTTP and requires no authentication.

Claude Desktop / Cursor / Windsurf

{
  "mcpServers": {
    "ai-dev-jobs": {
      "url": "https://aidevboard.com/mcp"
    }
  }
}

No API key or authentication is required.

Available Tools

search_jobs

Search the job index by keyword, location, company, or work arrangement. Returns matching listings with title, company, location, and salary information.

search_jobs({ query: "machine learning engineer", location: "remote" })

get_job

Retrieve full details for a specific job listing by ID, including description, requirements, salary range, and application link.

get_job({ id: "abc123" })

list_companies

List all companies in the index with their open position counts. Useful for discovering which companies are actively hiring.

list_companies({})

get_company

Retrieve details for a specific company, including available AI roles when exposed by the endpoint.

get_company({ id: "openai" })

get_stats

Get aggregate statistics about the job market: total listings, top companies by open roles, role distribution, and location breakdown.

get_stats({})

match_jobs

Match jobs against a candidate profile, skills list, or preferences.

match_jobs({ skills: ["python", "llm", "pytorch"], workplace: "remote" })

get_salary_data

Retrieve salary statistics for roles, tags, levels, or locations when available.

get_salary_data({ tag: "llm", level: "senior" })

list_tags

List indexed tags that can be used to filter searches or salary analysis.

list_tags({})

Examples

Example 1: Find Remote ML Jobs

Use @ai-dev-jobs-mcp to find remote machine learning engineer positions.

The agent will call search_jobs({ query: "machine learning engineer", location: "remote" }) and return matching listings.

Example 2: Check Which Companies Are Hiring

Use @ai-dev-jobs-mcp to list all companies currently hiring for AI roles.

The agent will call list_companies({}) and return companies sorted by number of open positions.

Example 3: Get Job Market Overview

Use @ai-dev-jobs-mcp to show current AI job market statistics.

The agent will call get_stats({}) and return aggregate data on listings, top employers, and role distribution.

Example 4: Get Full Job Details

Use @ai-dev-jobs-mcp to get the full details for job ID abc123.

The agent will call get_job({ id: "abc123" }) and return the complete listing with requirements and application link.

Example 5: Match Jobs to a Candidate Profile

Use @ai-dev-jobs-mcp to match remote LLM roles to a senior Python and PyTorch profile.

The agent will call match_jobs({ skills: ["python", "llm", "pytorch"], workplace: "remote" }) and return suitable listings.

Example 6: Compare Salary Data

Use @ai-dev-jobs-mcp to compare senior LLM salary data.

The agent will call get_salary_data({ tag: "llm", level: "senior" }) and summarize available compensation ranges.

Best Practices

• Use search_jobs with specific keywords for targeted results rather than broad queries
• Use list_companies to discover companies, then search_jobs filtered by company name for focused searches
• Use get_stats to provide users with market context before diving into specific listings
• Use match_jobs when the user gives skills, seniority, location, or work arrangement preferences
• Use get_salary_data only as market context; remind users that listings and compensation change quickly
• Combine with resume or cover letter skills to create end-to-end job application workflows

Limitations

• The index covers AI and ML roles specifically; general software engineering jobs outside the AI space may not be included.
• Job listings are refreshed regularly but may have a short delay before new postings appear.
• Salary data is available when companies provide it; not all listings include salary information.
• Counts and salary medians are live market data and should be refreshed with get_stats before quoting them in user-facing output.

Related Skills

• @not-human-search-mcp - Discover AI-ready tools and APIs via MCP
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