How to Use the HrFlow.ai MCP in Claude Code

Q: How do I install the HrFlow.ai server for Claude Code?

Use the command line to run claude mcp add with the server URL. Once added, you can verify the connection with claude mcp list.

Q: Can I automate resume parsing with HrFlow.ai and Claude Code?

Yes. You can trigger parseprofile within your shell scripts to process batches of resumes. It's designed for headless execution in your backend workflows.

Q: How do I pass my API key to HrFlow.ai in Claude Code?

Set the HRFLOWAPIKEY as an environment variable in your terminal session. The server picks it up automatically when it initializes.

Run the HrFlow.ai MCP server with Claude Code for headless, terminal-based candidate parsing and automated job matching.

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Connect HrFlow.ai MCP to Claude Code

Create your Vinkius account to connect HrFlow.ai to Claude Code 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 Code

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Claude Code handles talent data in the terminal

Pipe candidate data straight through your CI/CD pipelines using `parse_profile`. It turns raw files into structured data without a GUI in sight. Once parsed, you can use `score_profiles` to rank applicants automatically. It's built for developers who want to run hiring logic as a background job.

Search and list jobs with Claude Code

Use `search_jobs` to find relevant roles from your terminal. It returns the data in a format you can easily pipe into other tools or shell scripts. If you need to audit your boards, `list_jobs` gives you a quick snapshot of your active listings. You control the entire flow with single commands.

Deep profile analysis using Claude Code

Analyze career histories instantly with `unfold_profile`. It gives you the breakdown of a candidate's professional path without opening a browser. Follow this with `ask_profile` to get quick answers about a candidate's experience. You get the facts you need to make a decision, right in your terminal.

Setup guide

Set up HrFlow.ai MCP in Claude Code

Prerequisites

Claude Code CLI installed (npm install -g @anthropic-ai/claude-code)
Active Vinkius subscription with a valid endpoint token

1

Run the add command

Open your terminal and run the command shown on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com. Use --scope user to make it available across all projects.
2

Verify the connection

Start a Claude Code session and type /mcp to list connected servers. You should see hrflowai-mcp with a green status indicator.
3

Start using tools

Ask Claude Code something like "Check my latest HrFlow.ai transactions." It will automatically discover and invoke the available HrFlow.ai tools.

Terminal

claude mcp add --transport http hrflowai-mcp https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Get your connection token →

Prerequisites

Claude Code CLI installed
Active Vinkius subscription with a valid endpoint token

1

Open the config file

Create or edit .mcp.json in your project root for project-level scope, or ~/.claude.json for user-level scope.
2

Add the HrFlow.ai MCP

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

Restart Claude Code

Start a new Claude Code session. Type /mcp to confirm the server is connected. The tools will be automatically available in your conversation.

.mcp.json

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

Get your connection token →

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 Code

Use the command line to run `claude mcp add` with the server URL. Once added, you can verify the connection with `claude mcp list`.

Yes. You can trigger `parse_profile` within your shell scripts to process batches of resumes. It's designed for headless execution in your backend workflows.

It does. You can run the server inside a container and connect via the standard HTTP transport. It's built to handle headless environments efficiently.

Set the `HRFLOW_API_KEY` as an environment variable in your terminal session. The server picks it up automatically when it initializes.

We use a zero-trust approach where your candidate profiles are only available during the execution of your task. No data is stored, and everything is wiped once the process finishes.

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