mcpbeat

Resume Optimizer MCP Server

local only

Resume Optimizer runs on your own machine — the client starts it, so there is no endpoint to ping. 1 installs a week from npm.

Resume analysis, ATS compatibility checks, bullet improvements, job-tailored optimization

1
Installs / week
npm · resume-optimizer
Stars
on GitHub
Last commit
0 releases in 90 days
License
language unknown

Connect this server

This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.

run in your terminal
claude mcp add resume-optimizer -- npx -y resume-optimizer
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "resume-optimizer": {
      "args": [
        "-y",
        "resume-optimizer"
      ],
      "command": "npx"
    }
  }
}
~/.codex/config.toml
[mcp_servers.resume-optimizer]
command = "npx"
args = ["-y", "resume-optimizer"]
.cursor/mcp.json
{
  "mcpServers": {
    "resume-optimizer": {
      "args": [
        "-y",
        "resume-optimizer"
      ],
      "command": "npx"
    }
  }
}
.vscode/mcp.json
{
  "mcpServers": {
    "resume-optimizer": {
      "args": [
        "-y",
        "resume-optimizer"
      ],
      "command": "npx"
    }
  }
}

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Resume Optimizer — questions

Answers built from our own checks of this server.

Why is there no uptime for Resume Optimizer?
Resume Optimizer runs on your own machine over stdio — there is no network address to reach, so uptime cannot be measured for it by anyone. What can be measured is adoption: the npm package resume-optimizer was installed 1 times last week.
How do I connect Resume Optimizer?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It runs locally, so the command pulls resume-optimizer straight from npm; nothing to host, nothing to sign up for.
How many people use Resume Optimizer?
The npm package resume-optimizer was installed 1 times in the last week. We show installs rather than GitHub stars on purpose: a star is a bookmark, an install is someone actually running it.