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.

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.

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.

Verba MCP Server for OpenAI Agents SDK 6 tools — connect in under 2 minutes

Name: Verba
Availability: InStock
Author: Vinkius

openai.github.io/openai-agents-python/mcp

Built by Vinkius GDPR 6 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Verba through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="Verba Assistant",
            instructions=(
                "You help users interact with Verba. "
                "You have access to 6 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from Verba"
        )
        print(result.final_output)

asyncio.run(main())

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* 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 Verba MCP Server

Intertwine the open-source Verba (by Weaviate) ecosystem natively into your conversational AI IDE. Execute powerful Retrieval-Augmented Generation processes and manage your localized knowledge bases simply by chatting.

The OpenAI Agents SDK auto-discovers all 6 tools from Verba through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Verba, another analyzes results, and a third generates reports, all orchestrated through Vinkius.

What you can do

Augmented Queries — Cast a question to your agent and have it retrieve fully synthesized answers from the Verba engine completely backed up by exact document citations.
Knowledge Management — Insert new context text, list all ingested documents, retrieve the deeply embedded raw data of any ID, or remove dead knowledge dynamically without Web UIs.
Health Checks — Request system configurations directly via chat to ensure your local LLM connections, embedding models, and cluster health are firing effectively.

The Verba MCP Server exposes 6 tools through the Vinkius. Connect it to OpenAI Agents SDK 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 Verba to OpenAI Agents SDK via MCP

Follow these steps to integrate the Verba MCP Server with OpenAI Agents SDK.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 6 tools from Verba

Why Use OpenAI Agents SDK with the Verba MCP Server

OpenAI Agents SDK provides unique advantages when paired with Verba through the Model Context Protocol.

Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

Verba + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Verba MCP Server delivers measurable value.

Automated workflows: build agents that query Verba, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents. one queries Verba, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through Verba tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query Verba to resolve tickets, look up records, and update statuses without human intervention

Verba MCP Tools for OpenAI Agents SDK (6)

These 6 tools become available when you connect Verba to OpenAI Agents SDK via MCP:

add_knowledge_document

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

delete_knowledge_document

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

get_document_details

Retrieves the full content and metadata of a specific document

get_system_config

Retrieves the current Verba system configuration

list_knowledge_documents

Lists all documents indexed in the Verba knowledge base

perform_rag_query

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

Example Prompts for Verba in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Verba immediately.

"Check Verba's configuration to see which embedding model it is currently using."

"Perform a RAG query asking: 'What are our key deployment steps based on the infrastructure guide?'"

"List all documents and output the unique ID of the 'Employee Code of Conduct' file."

Troubleshooting Verba MCP Server with OpenAI Agents SDK

Common issues when connecting Verba to OpenAI Agents SDK through the Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

Verba + OpenAI Agents SDK FAQ

Common questions about integrating Verba MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.