How to Use the HrFlow.ai MCP in Cursor

Q: How do I add the HrFlow.ai server to my Cursor editor?

Create a .cursor/mcp.json file in your project root or modify your global MCP settings. Add the server under the mcpServers key with your credentials, and the tools will become available in Cursor's Agent mode immediately.

Q: Can Cursor write code using live HrFlow.ai candidate data?

Yes. When you use Agent mode in Cursor, the model calls listprofiles or searchprofiles to fetch real candidate structures. It then uses those live schemas to write accurate, production-ready parsing and matching code.

Q: How do I debug HrFlow.ai scoring logic inside Cursor?

You run the scoreprofiles tool directly in your chat sidebar. This lets you check how candidates match against specific job descriptions and adjust your code logic based on the raw scores returned by the API.

Q: Can I search for jobs using semantic filters in the editor?

Yes. The searchjobs tool lets you execute semantic queries against your active boards. Your agent can run these searches to help you build and test job board integrations without leaving your code.

Generate code that matches, parses, and queries candidate profiles using HrFlow.ai directly inside Cursor.

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Connect HrFlow.ai MCP to Cursor

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Setup HrFlow.ai with Cursor

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Build automated parsing pipelines in Cursor

The `parse_profile` tool lets your Cursor agent process resume files and generate type-safe code based on the actual JSON output. Instead of writing mock data, you run this HrFlow.ai tool inside Cursor to get real candidate schemas to build your recruitment workflows. This means you can write, test, and debug your parsing logic in Cursor using this MCP Server. Your Cursor agent uses the live HrFlow.ai response to write precise TypeScript interfaces or Python models that match the exact structure of your processed resumes.

Test candidate scoring with this MCP Server

The `score_profiles` tool computes match ratings between candidates and job descriptions directly inside your Cursor editing environment. While writing your backend matching logic, your Cursor agent calls this HrFlow.ai tool to verify that your algorithms return correct scores. You can also call `unfold_profile` in Cursor to analyze career paths and generate test assertions based on real candidate histories. This speeds up your Cursor testing cycles because you are working with live HrFlow.ai talent data instead of static stubs.

Query active job boards and sources inside Cursor

The `list_boards` and `list_sources` tools pull your active HrFlow.ai hiring channels directly into your Cursor MCP workspace. You can query your actual HrFlow.ai recruitment channels to verify connection strings and database mappings while writing API integrations in Cursor. Your Cursor agent runs `search_jobs` to pull live HrFlow.ai listings and write queries that filter jobs by department or location. This eliminates the context switching of opening a browser to check if your HrFlow.ai API calls return the right fields while coding in Cursor.

Setup guide

Set up HrFlow.ai MCP in Cursor

Prerequisites

Cursor installed (macOS, Windows, or Linux)
Active Vinkius subscription with a valid endpoint token

1

Open MCP Settings

Go to Cursor Settings → MCP or open the Command Palette (Cmd+Shift+P / Ctrl+Shift+P) and search for "MCP: Add Server".
2

Add the HrFlow.ai MCP

Cursor will create or open .cursor/mcp.json in your project root. Paste the JSON snippet on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Enable Agent mode

Open Composer (Cmd+I / Ctrl+I) and switch to Agent mode using the dropdown at the top. MCP tools are only available in Agent mode.
4

Verify the connection

Ask Cursor something like "List my recent HrFlow.ai transactions." If the MCP tools are loaded correctly, Cursor will call the HrFlow.ai tools automatically. You can also check Settings → MCP for a green status indicator.

.cursor/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 Cursor

Create a `.cursor/mcp.json` file in your project root or modify your global MCP settings. Add the server under the `mcpServers` key with your credentials, and the tools will become available in Cursor's Agent mode immediately.

Yes. When you use Agent mode in Cursor, the model calls `list_profiles` or `search_profiles` to fetch real candidate structures. It then uses those live schemas to write accurate, production-ready parsing and matching code.

You run the `score_profiles` tool directly in your chat sidebar. This lets you check how candidates match against specific job descriptions and adjust your code logic based on the raw scores returned by the API.

Yes. The `search_jobs` tool lets you execute semantic queries against your active boards. Your agent can run these searches to help you build and test job board integrations without leaving your code.

Yes. Your candidate resumes and job profiles are queried through a zero-trust, ephemeral connection. The server does not store your API keys or candidate details, keeping your talent acquisition data isolated in your local workspace.

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Connect this server to Cursor, Claude, VS Code, and more.

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