How to Use the Jina AI MCP in Cursor

Q: How do I configure the Jina AI MCP Server in Cursor?

Add the server details to your .cursor/mcp.json file in your project root. Once saved, Cursor Agent mode can immediately access the search and reading tools.

Q: Can Cursor use Jina AI to generate vector embeddings?

Yes, Cursor can call getembeddings directly through the server. This lets your agent generate and test vector representations of your local code or text files on the fly.

Q: Can I use this server to rank code search results?

Yes, your agent can use rerankdocuments to sort through code snippets or documentation files in your workspace. It helps Cursor find the most relevant context for your current coding task.

Feed clean web search results and accurate embeddings directly into Cursor Agent mode.

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Connect Jina AI MCP to Cursor

Create your Vinkius account to connect Jina AI 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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Setup Jina AI with Cursor

Ask AI about this MCP

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Claude

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Let Cursor write code with live web data

Stop writing code against outdated API documentation. When you run Cursor in Agent mode, this MCP Server helps Cursor write functional code by using `search_web` to pull the latest API specs and library updates directly into your active coding session. The agent then uses `read_url` to parse the exact documentation page you need. Cursor writes functional code based on current web standards instead of guessing based on training data from two years ago.

Build vector search pipelines inside Cursor

If you are building search features, you need to test embeddings quickly. This MCP Server lets your Cursor agent run `get_embeddings` on your source code or documentation files to generate vectors instantly. You can also test how your search results sort by letting the agent use `rerank_documents` on your test data. You see exactly how the scoring works without leaving your editor or running separate terminal scripts.

Audit facts and tokens inside your workspace

When writing technical blogs or documentation in Cursor, your agent can call `check_fact` to verify technical claims. It keeps your markdown files accurate without forcing you to open a browser tab to search. Before pushing large prompt templates to production, let Cursor use `tokenize_text` to check the exact token footprint of your code files. This keeps your API costs predictable before you deploy.

Setup guide

Set up Jina 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 Jina 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 Jina AI transactions." If the MCP tools are loaded correctly, Cursor will call the Jina AI tools automatically. You can also check Settings → MCP for a green status indicator.

.cursor/mcp.json

{
  "mcpServers": {
    "jina-ai-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 Jina 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 Jina AI MCP in Cursor

Add the server details to your `.cursor/mcp.json` file in your project root. Once saved, Cursor Agent mode can immediately access the search and reading tools.

Yes, Cursor can call `get_embeddings` directly through the server. This lets your agent generate and test vector representations of your local code or text files on the fly.

Standard search often returns messy HTML that confuses the editor. This tool uses `search_web` and `read_url` to return clean markdown, helping Cursor write better code with less noise.

Yes, your agent can use `rerank_documents` to sort through code snippets or documentation files in your workspace. It helps Cursor find the most relevant context for your current coding task.

Only the specific text snippets, search terms, or URLs you pass to `get_embeddings` or `search_web` are sent to Jina's API. Your local workspace files in Cursor remain completely private and are never scanned or uploaded.

Use it with your favorite AI tools

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

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