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ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use Verba with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Connect your Verba RAG platform to your AI agent. Search your documents, retrieve semantic answers, and manage your Weaviate knowledge base directly.

Included with plan

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Complete set · 6 capabilities

The complete Verba capability set.

These are the exact actions your AI can choose when you ask it to work with Verba.

Capability set01 / 02

01-03

3 capabilities in this set.

Part of 6 available through Verba.

  1. 01

    Delete knowledge document

    This action is irreversible. Permanently removes a document from the knowledge base

  2. 02

    Get document details

    Retrieves the full content and metadata of a specific document

  3. 03

    List knowledge documents

    Lists all documents indexed in the Verba knowledge base

Capability set02 / 02

04-06

3 capabilities in this set.

Part of 6 available through Verba.

  1. 04

    Add knowledge document

    Provide the document content and optional metadata JSON. Ingests a new document into the Verba knowledge base

  2. 05

    Get system config

    Retrieves the current Verba system configuration

  3. 06

    Perform rag query

    Returns summarized answers with citations. Executes a RAG (Retrieval Augmented Generation) query against the Verba knowledge base

Observed, not estimated

841ms average. Fast in production.

Verba is checked daily against the live service.

Daily averagePeak 1010ms
Aug 20Today
Fastest day
683ms
Slowest day
1010ms
14-day trend
Slowing+11%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 6 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Verba, so you can see the experience inside your AI.

It does not authenticate your account with Verba. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Verba Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_mosNtker0LQyevIfUh7gGdgJqJOKEbbiUG4YbxIE/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Verba capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "verba-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_mosNtker0LQyevIfUh7gGdgJqJOKEbbiUG4YbxIE/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

FAQ

Questions Verba owners ask.

  • 01

    Can I query my local Verba instance directly through Cursor?

    Yes! Once you configure VERBA_API_URL to point to http://localhost:8000 (or your host port), you can prompt your AI assistant to execute rigorous perform_rag_query instructions without ever breaking your developer focus.

  • 02

    How do I insert fresh text data into Verba completely using conversational chat?

    Provide the agent with your desired context directly. For example: Add this chunk of markdown as a new document to Verba: '# Title Content...'. The agent leverages addDocumentTool, serializes the payload, and commits it into Verba's vector store immutably.

  • 03

    Are the query answers backed by citations from its embedded documents?

    Absolutely. That's the primary benefit of the integration. When you run perform_rag_query, Verba utilizes Weaviate's hybrid search mechanics. The output explicitly includes natural language synthesis backed by the unique document IDs and snippet texts it referenced.

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