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How to Use the Marketaux MCP in Cursor

Feed real-time market sentiment and stock data directly to Cursor to generate code using live financial news.

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Connect Marketaux MCP to Cursor

Create your Vinkius account to connect Marketaux to Cursor 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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Build Apps in Cursor with Live Marketaux Data

The `get_latest_news` tool lets your agent pull real-time financial articles directly into your active code workspace. Instead of writing code against hardcoded mock JSON, Cursor calls the live API to build and test your data parsers. You can run `search_news` to query specific global events and see the exact payload structure your application will handle. This lets you write precise TypeScript interfaces or Python models based on actual API responses.

Test Sentiment Algorithms Using Cursor Agent

The `get_sentiment_analysis` tool connects news sentiment analysis directly to your editor's agent mode. When building trading algorithms, you can tell Cursor to analyze the returned sentiment scores and write execution logic based on those metrics. That's the play if you want to write test cases that simulate high-volatility events. Because the agent has direct access to `get_trending_news`, it can write test cases that handle real-world market chatter without leaving your development environment.

Run Financial Queries via MCP Server

The `get_entities` tool retrieves structured data on companies, industries, and indices tracked by the API. Cursor uses this tool to help you write data pipelines that clean and normalize chaotic financial datasets. Combine this with `get_symbols` and `list_industries` to build autocomplete features or database seed scripts. Your editor's agent accesses these tools to populate your local database schemas with valid market metadata.

Setup guide

Set up Marketaux MCP in Cursor

Prerequisites

  • Cursor installed (macOS, Windows, or Linux)
  • Active Vinkius subscription with a valid endpoint token
  1. 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. 2

    Add the Marketaux 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. 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. 4

    Verify the connection

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

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

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Marketaux. 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 Marketaux MCP in Cursor

Add the server configuration to your global or project-specific `mcp.json` file under the `mcpServers` key. Once added, enable Agent mode in your chat panel to start calling the financial news tools.
Yes, Cursor calls `get_latest_news` or `search_news` during a chat session to inspect real payloads. It then writes functional code tailored to the exact structure of those financial news feeds.
Yes, the `search_exchanges` tool is fully accessible to the Cursor agent. You can ask the agent to find a specific exchange code and immediately write code to query listings on that exchange.
The agent calls `get_sentiment_analysis` to fetch articles with pre-calculated sentiment metrics. It can then write conditional logic in your code to trigger actions when sentiment crosses your specified thresholds.
Your API key is stored locally in your environment variables and passed securely to the sandboxed runtime. The financial news queries and ticker symbols you analyze are sent directly to the API endpoint without intercepting your proprietary trading logic.

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