ParseHub MCP Server for Cursor 10 tools — connect in under 2 minutes
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.
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{
"mcpServers": {
"parsehub": {
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}
}
}
* 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 ParseHub MCP Server
Bring ParseHub Cloud Scraping directly into your AI workflows. Manage pre-configured web scraping targets natively and orchestrate complex headless browser automation directly from chat. Dispatch run jobs on command, query execution status limits, and extract final parsed payloads securely.
Cursor's Agent mode turns ParseHub into an in-editor superpower. Ask Cursor to generate code using live data from ParseHub 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.
What you can do
- Project Navigation — Inspect and list configured ParseHub projects, determining start URLs, templates, and total crawler pages attached
- Execution Dispatch — Command remote servers to trigger specific headless data extraction jobs
run_projectoptionally overriding starting URLs natively - Observability Tracing — Monitor exactly where a
Runobject is (queued, initialized, running, complete) without checking the desktop app - Payload Extraction — Pull down structured arrays containing the scraped payloads securely via
get_run_datamatching explicit datasets
The ParseHub 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 ParseHub to Cursor via MCP
Follow these steps to integrate the ParseHub 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 ParseHub
Open Agent mode in chat and ask: "Using ParseHub, help me..." — 10 tools available
Why Use Cursor with the ParseHub MCP Server
Cursor AI Code Editor provides unique advantages when paired with ParseHub 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
ParseHub + Cursor Use Cases
Practical scenarios where Cursor combined with the ParseHub 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
ParseHub MCP Tools for Cursor (10)
These 10 tools become available when you connect ParseHub to Cursor via MCP:
cancel_run
If the run was already scraping pages, partial data may be available. Data from already-scraped pages is preserved and can be retrieved with get_run_data. Use this to stop long-running scrapes or free up queue slots. Cancel a queued or actively running ParseHub run
delete_run
Cannot be undone. Use this to clean up old runs and free up storage quota on your account. Permanently delete a ParseHub run and its extracted data
get_last_ready_data
Ideal for dashboards or integrations that always want the freshest available data without managing individual run tokens. Instantly get the latest completed data for a ParseHub project
get_project
The project_token can be found via list_projects or in the ParseHub desktop client settings tab. Get detailed configuration of a specific ParseHub project
get_run_data
Only works when the run status is "complete" and data_ready is true. The JSON structure mirrors the template selection configuration set up in the ParseHub desktop client. Download the raw JSON data extracted from a completed ParseHub run
get_run_details
Poll this endpoint to wait for a run to complete before fetching data. Check the status of a specific ParseHub run
list_projects
Each project includes a project_token (unique identifier), title, last_run timestamp, and template configuration. Use the project_token for all subsequent run management operations. List all ParseHub web scraping projects
list_runs
Useful for auditing or finding a specific completed run to fetch data from. Get the history of all runs for a ParseHub project
run_project
Returns a run_token for tracking progress. The run enters a queue and begins processing within seconds. Use get_run to monitor and get_run_data to retrieve results once complete. Start a new ParseHub scraping run for a project
run_project_with_url
Perfect for scraping different pages with the same template (e.g., different product categories). The template extraction rules still apply unchanged — only the starting page changes. Start a ParseHub run targeting a custom URL instead of the project default
Example Prompts for ParseHub in Cursor
Ready-to-use prompts you can give your Cursor agent to start working with ParseHub immediately.
"Fetch the list of scrape projects I have on my ParseHub account."
"Start a new run for project 't9zx...' and check its status."
"Extract the finished data JSON payload from run ID 'run_k1l'."
Troubleshooting ParseHub MCP Server with Cursor
Common issues when connecting ParseHub to Cursor through the Vinkius, and how to resolve them.
Tools not appearing in Cursor
Server shows as disconnected
ParseHub + Cursor FAQ
Common questions about integrating ParseHub MCP Server with Cursor.
What is Agent mode and why does it matter for MCP?
Where does Cursor store MCP configuration?
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?
How do I verify MCP tools are loaded?
Connect ParseHub with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect ParseHub to Cursor
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.
