How to Use the Vectara MCP in Cursor

Q: How does Cursor manage data sources with Vectara?

You configure the server in .cursor/mcp.json. This allows the AI agent to access all indexed corpora, making your code context-aware of your project's entire knowledge base.

Q: Can I list all my corpora using Vectara and Cursor?

Absolutely. The listcorpora tool provides a quick overview of every searchable dataset in your account, letting you know what data sources are available for coding context.

Q: What specific data does Vectara and Cursor touch when listing documents?

When running listcorpusdocuments, you get a list of indexed document IDs and their metadata. This confirms exactly which pieces of text are ready for the agent to read.

Get live data context injected directly into your code using Cursor's Agent mode.

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Connect Vectara MCP to Cursor

Create your Vinkius account to connect Vectara 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 Vectara with Cursor

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Injecting Live Context into Code

When you run `perform_semantic_search`, the agent doesn’t just summarize results; it passes the live data to your code. This means you're writing functions that use real API responses, not mock stubs or fake context.

Executing Grounded Code Chats

Use `execute_rag_chat` while coding. Give it the relevant corpus keys and your query; the agent returns a summarized answer with citations that you can instantly reference in the function body you're writing.

Managing Project Data Sources

Your project needs multiple knowledge bases. The `list_corpora` tool lets you see all available datasets, and `get_corpus_details` helps you verify the configuration for each one before your agent tries to connect.

Setup guide

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

.cursor/mcp.json

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

Get your connection token →

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Common questions about Vectara MCP in Cursor

You configure the server in `.cursor/mcp.json`. This allows the AI agent to access all indexed corpora, making your code context-aware of your project's entire knowledge base.

This permanently removes a document from the corpus. If you delete an indexed document, any code generated that relies on it will need to be updated.

Absolutely. The `list_corpora` tool provides a quick overview of every searchable dataset in your account, letting you know what data sources are available for coding context.

Yes. The agent uses real API responses derived from corpus searches; it never injects mock or simulated data, so you can trust the context within your functions.

When running `list_corpus_documents`, you get a list of indexed document IDs and their metadata. This confirms exactly which pieces of text are ready for the agent to read.

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