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Careerproof

@dontellu77

About Careerproof

Career and workforce intelligence built on a deep HR ontology — skill taxonomies, role definitions and responsibilities, compensation and incentive structures, learning and development pathways, sourcing strategies, and role/skill evolution mapping. This structured foundation, co

Basic information

Category

AI & Agents

Transports

stdio

Publisher

dontellu77

Submitted by

Admin

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "careerproof": {
      "url": "https://mcp.careerproof.ai/mcp"
    }
  }
}

Tools

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We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Careerproof?

Careerproof is an AI-powered career and workforce intelligence platform for professionals and organizations. It integrates with Claude Code and Gemini CLI via an MCP server, providing 42 tools and 6 slash-command skills for tasks like CV optimization, candidate evaluation, salary benchmarking, and workforce planning. The platform is powered by a curated RAG knowledge base from 50+ premium sources and live web research via Tavily.

How to use Careerproof?

Install the plugin in Claude Code using two commands: /plugin marketplace add dontellu77/careerproof-claude-skills then /plugin install careerproof-skills@careerproof. For Gemini CLI, install skills via a shell script and connect the MCP server with a bearer token. After authentication (OAuth for Claude Code, API key for others), invoke skills by name, e.g., /atlas-onboard or /ceevee-optimize, or use MCP tools directly in conversation.

Key features of Careerproof

  • 42 MCP tools covering the full Careerproof API
  • 6 guided slash-command skills (Atlas and CeeVee workflows)
  • Automatic OAuth authentication – no API keys to manage
  • Dual mode: personal career intelligence (CeeVee) and workforce intelligence (Atlas)
  • Intelligence engine: expert-curated RAG from 50+ premium sources + live web research via Tavily
  • Analysis calibrated to CV/candidate context (role, seniority, industry, skills)

Use cases of Careerproof

  • A professional optimizes their CV positioning and gets data-backed career advice using CeeVee skills
  • An HR leader batch evaluates candidates against a job description with competency scoring
  • A talent acquisition team generates a salary benchmarking report for a senior role in London
  • An org design consultant produces a research-grade workforce report without expensive consulting
  • A career coach uses the career intelligence chat with live web research to advise clients

FAQ from Careerproof

What does Careerproof do that generic AI assistants cannot?

Careerproof grounds its analysis in a curated RAG knowledge base from 50+ premium sources (HBR, McKinsey, BCG, Gartner, etc.) and live web research via Tavily, rather than stale training data. Its intelligence is calibrated to actual experience when a CV is provided, and it offers structured, research-backed outputs for both individual career decisions and organizational workforce strategy.

How do I authenticate with Careerproof?

In Claude Code, OAuth is built in – on first use, a browser window opens for you to log in, and tokens are managed automatically. For Gemini CLI or programmatic access, you configure a bearer token (a cpk_... API key) in the MCP server configuration. Get your API key at careerproof.ai.

What are the requirements to use Careerproof?

You need an active CareerProof account with available credits, plus either Claude Code or Gemini CLI. You can sign up at careerproof.ai.

How much do the skills cost in credits?

Skill costs are listed in the README: atlas-shortlist 8–13 credits per candidate, atlas-deep-eval ~26 credits, atlas-report 15 credits, ceevee-optimize 10–13 credits, ceevee-career-intel 2 credits per message. The atlas-onboard skill is free.

Can I use the MCP tools without the slash-command skills?

Yes. When the MCP server is connected, you get direct access to all 42 tools in the conversation. For example, you can say "Upload this CV and run a competency analysis" and the model will use the appropriate tools.

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