How do I get HrFlow API credentials?

You can find your X-API-KEY in the HrFlow dashboard under Settings > API. You also need the email address of your account.

Can I parse PDF resumes with this MCP?

Yes, the parse_profile tool allows you to provide a public URL to a resume file for AI parsing.

What is profile asking?

It's an AI feature that lets you ask questions about a candidate's profile in plain English and get intelligent answers based on their data.

HrFlow.ai MCP Server for Cursor 10 tools — connect in under 2 minutes

Name: HrFlow.ai
Availability: InStock
Author: Vinkius

docs.cursor.com/context/model-context-protocol

Built by Vinkius GDPR 10 Tools IDE

Cursor is an AI-first code editor built on VS Code that integrates LLM-powered coding assistance directly into the development workflow. Its Agent mode enables autonomous multi-step coding tasks, and MCP support lets agents access external data sources and APIs during code generation.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

RecommendedModern Approach — Zero Configuration

Vinkius Desktop App

The modern way to manage MCP Servers — no config files, no terminal commands. Install HrFlow.ai and 2,500+ MCP Servers from a single visual interface.

Download Free Open SourceNo signup required

Classic Setup·json

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

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About HrFlow.ai MCP Server

Empower your AI agents with HrFlow.ai's advanced talent acquisition capabilities. This MCP server allows you to parse resumes, search profiles and jobs with semantic filters, score candidates against job descriptions, and ask natural language questions about profiles. Ideal for automating recruitment workflows with AI-driven insights.

Cursor's Agent mode turns HrFlow.ai into an in-editor superpower. Ask Cursor to generate code using live data from HrFlow.ai and it fetches, processes, and writes. all in a single agentic loop. 10 tools appear alongside file editing and terminal access, creating a unified development environment grounded in real-time information.

The HrFlow.ai MCP Server exposes 10 tools through the Vinkius. Connect it to Cursor in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect HrFlow.ai to Cursor via MCP

Follow these steps to integrate the HrFlow.ai MCP Server with Cursor.

Open MCP Settings

Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"

Add the server config

Paste the JSON configuration above into the mcp.json file that opens

Save the file

Cursor will automatically detect the new MCP server

Start using HrFlow.ai

Open Agent mode in chat and ask: "Using HrFlow.ai, help me...". 10 tools available

Why Use Cursor with the HrFlow.ai MCP Server

Cursor AI Code Editor provides unique advantages when paired with HrFlow.ai through the Model Context Protocol.

Agent mode turns Cursor into an autonomous coding assistant that can read files, run commands, and call MCP tools without switching context

Cursor's Composer feature can generate entire files using real-time data fetched through MCP. no copy-pasting from external dashboards

MCP tools appear alongside built-in tools like file reading and terminal access, creating a unified agentic environment

VS Code extension compatibility means your existing workflow, keybindings, and extensions all work alongside MCP tools

HrFlow.ai + Cursor Use Cases

Practical scenarios where Cursor combined with the HrFlow.ai MCP Server delivers measurable value.

Code generation with live data: ask Cursor to generate a security report module using live DNS and subdomain data fetched through MCP

Automated documentation: have Cursor query your API's tool schemas and generate TypeScript interfaces or OpenAPI specs automatically

Infrastructure-as-code: Cursor can fetch domain configurations and generate corresponding Terraform or CloudFormation templates

Test scaffolding: ask Cursor to pull real API responses via MCP and generate unit test fixtures from actual data

HrFlow.ai MCP Tools for Cursor (10)

These 10 tools become available when you connect HrFlow.ai to Cursor via MCP:

ask_profile

Asks a natural language question about a specific profile

list_boards

Lists job boards

list_jobs

Lists jobs stored in HrFlow boards

list_profiles

Lists candidate profiles stored in HrFlow

list_sources

Lists profile sources

parse_profile

Parses a resume file into a structured profile

score_profiles

Scores candidate profiles against a specific job

search_jobs

Searches for jobs with semantic filters

search_profiles

Searches for profiles with semantic filters

unfold_profile

Analyzes and unfolds the career path of a profile

Example Prompts for HrFlow.ai in Cursor

Ready-to-use prompts you can give your Cursor agent to start working with HrFlow.ai immediately.

"List the last 5 profiles added to my HrFlow source."

"Ask profile key 'abc-123' if they have experience with Kubernetes."

"Find jobs that match candidate 'john-doe-key'."

Troubleshooting HrFlow.ai MCP Server with Cursor

Common issues when connecting HrFlow.ai to Cursor through the Vinkius, and how to resolve them.

Tools not appearing in Cursor

Ensure you are in Agent mode (not Ask mode). MCP tools only work in Agent mode.

Server shows as disconnected

Check Settings → Features → MCP and verify the server status. Try clicking the refresh button.

HrFlow.ai + Cursor FAQ

Common questions about integrating HrFlow.ai MCP Server with Cursor.

What is Agent mode and why does it matter for MCP?

Agent mode is Cursor's autonomous execution mode where the AI can perform multi-step tasks: reading files, editing code, running terminal commands, and calling MCP tools. Without Agent mode, Cursor operates in a simpler ask-and-answer mode that doesn't support tool calling. Always ensure you're in Agent mode when working with MCP servers.

Where does Cursor store MCP configuration?

Cursor looks for MCP server configurations in a mcp.json file. You can configure servers at the project level (.cursor/mcp.json in your project root) or globally (~/.cursor/mcp.json). Project-level configs take precedence.

Can Cursor use MCP tools in inline edits?

No. MCP tools are only available in Agent mode through the chat panel. Inline completions and Tab suggestions do not trigger MCP tool calls. This is by design. tool calls require user visibility and approval.

How do I verify MCP tools are loaded?

Open Settings → Features → MCP and look for your server name. A green indicator means the server is connected. You can also check Agent mode's available tools by clicking the tools dropdown in the chat panel.