How to Use the HrFlow.ai MCP in Claude

Q: How do I configure HrFlow.ai on my Claude Desktop app?

Open your claudedesktopconfig.json file and add the server configuration under the mcpServers block. Provide your API key as an environment variable, restart the app, and look for the hammer icon in your chat window to start using the tools.

Q: Can I use HrFlow.ai on Claude Desktop to parse local resumes?

Yes. The parseprofile tool reads local candidate files directly from your computer when you run the server via stdio on Claude Desktop. This lets you convert raw PDFs into structured data profiles without manual uploads.

Q: How do I ask specific questions about a candidate's background?

Use the askprofile tool inside your chat window. It lets you write natural language questions about a specific profile, and the model queries the parsed resume data directly to give you a straight answer.

Run HrFlow.ai talent search and resume parsing pipelines directly inside your Claude Desktop workspace.

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Connect HrFlow.ai MCP to Claude Desktop

Create your Vinkius account to connect HrFlow.ai to Claude Desktop and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup HrFlow.ai with Claude Desktop

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Parse resumes directly inside Claude Desktop

The `parse_profile` tool converts messy PDF or Word resumes into structured JSON payloads right inside your local Claude Desktop chat interface. Instead of manual data entry, you drag a candidate file into Claude Desktop, and the HrFlow.ai parser instantly extracts skills, work history, and education. Because Claude Desktop runs as a local app, this MCP Server processes these files locally through your configured stdio transport to parse resumes. You get clean, structured HrFlow.ai candidate data without leaving your Claude Desktop conversation or copying text back and forth.

Score and match candidates with this MCP Server

The `score_profiles` tool matches applicant data against your open roles to rank the best fits directly inside Claude Desktop. Your Claude Desktop agent reads the job requirements, pulls candidate details from your HrFlow.ai database, and calculates match scores using your custom logic. Doing this inside Claude Desktop means you can ask follow-up questions about why a candidate scored a certain way in HrFlow.ai. You run `unfold_profile` inside Claude Desktop to analyze their career trajectory and see if their past promotions align with your team's growth needs.

Search jobs and boards through Claude Web

The `search_jobs` and `list_boards` tools connect your Claude Desktop setup to active HrFlow.ai hiring pipelines without loading a separate browser tab. You connect Claude Web to the remote endpoint, allowing your browser agent to pull live HrFlow.ai job descriptions and board statuses on demand. This setup lets you query open HrFlow.ai listings using natural language in Claude Desktop. Your Claude Desktop agent calls `search_profiles` to find candidates who match those active jobs, giving you a fast way to source talent without manual search strings.

Setup guide

Set up HrFlow.ai MCP in Claude Web or Desktop

1

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.
2

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL: https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.
3

Start a conversation

Open a new chat. The HrFlow.ai MCP tools are available immediately — no restart needed.

Endpoint URL

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

No configuration file needed — paste the URL directly in the Claude web interface.

Available on Free (1 connector), Pro, Max, Team, and Enterprise plans.

Prerequisites

Claude Desktop installed (macOS or Windows)
Active Vinkius subscription with a valid endpoint token

1

Open Claude Desktop Settings

Click the menu icon at the top-left corner, go to Settings → Developer → Edit Config. This opens claude_desktop_config.json in your default text editor.
2

Paste the HrFlow.ai MCP configuration

Copy the JSON snippet on the right into the mcpServers object. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Restart Claude Desktop

Close and reopen the application. Claude needs a full restart to load new MCPs — refreshing a conversation is not enough.
4

Verify the connection

Open a new conversation. Click the 🔌 icon at the bottom of the message input. You should see tools listed under hrflowai-mcp.

json

{
  "mcpServers": {
    "hrflowai-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by HrFlow.ai. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about HrFlow.ai MCP in Claude Desktop

Open your `claude_desktop_config.json` file and add the server configuration under the `mcpServers` block. Provide your API key as an environment variable, restart the app, and look for the hammer icon in your chat window to start using the tools.

Yes. The `parse_profile` tool reads local candidate files directly from your computer when you run the server via stdio on Claude Desktop. This lets you convert raw PDFs into structured data profiles without manual uploads.

You can connect to the web version of Claude using a remote URL instead of a local config. Go to your browser settings, add the custom connector, paste your hosted endpoint, and authenticate to run queries like `search_profiles` in your browser.

Use the `ask_profile` tool inside your chat window. It lets you write natural language questions about a specific profile, and the model queries the parsed resume data directly to give you a straight answer.

Your candidate resumes and matching scores are processed securely. Vinkius runs the server in an isolated V8 sandbox, meaning your raw applicant data and proprietary scores never persist on the hosting platform or leak to external systems.

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