Can my agent perform semantic RAG queries against my collections?

Yes. The 'rag_query' tool allows you to ask questions in natural language. The agent queries your vector store via Cognita and uses an LLM to synthesize a final answer based explicitly on the retrieved context.

How can I trigger a data ingestion pipeline through the agent?

Provide the collection name and the data source FQN (Fully Qualified Name). The 'ingest_data' tool will command the Cognita backend to start a sync, updating your RAG vector space with the latest remote documents.

Can I audit the raw document chunks before LLM generation?

Absolutely. Use the 'search_chunks' tool to perform vector searches that return raw text segments and metadata without LLM synthesis. This is the perfect way to verify that your retrieval logic is pulling the correct data boundaries.

Cognita (RAG Framework) MCP Server for OpenAI Agents SDK 7 tools — connect in under 2 minutes

Name: Cognita (RAG Framework)
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 7 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Cognita (RAG Framework) through the 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="Cognita (RAG Framework) Assistant",
            instructions=(
                "You help users interact with Cognita (RAG Framework). "
                "You have access to 7 tools."
            ),
            mcp_servers=[mcp_server],
        )

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

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Cognita (RAG Framework) MCP Server

Connect your Cognita (TrueFoundry) instance to any AI agent and take full control of your modular RAG workflows through natural conversation.

The OpenAI Agents SDK auto-discovers all 7 tools from Cognita (RAG Framework) through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries Cognita (RAG Framework), another analyzes results, and a third generates reports, all orchestrated through the Vinkius.

What you can do

Knowledge Collections — List and audit RAG collections to inspect embedding configurations, token lengths, and parser details
Data Ingestion — Force sync remote files from SQL, Cloud Storage, or APIs into your vector space to update your knowledge base
RAG Queries — Dispatch automated AI questions that query your vector store and synthesize accurate answers from stored context
Chunk Auditing — Perform lexical or semantic searches to pull raw document chunks and verify precise text segments
Model Registry — Enumerate available LLMs and embedding models registered inside your modular Cognita installation
DataSource Management — List all connected data sources to verify which external data is mapped into your AI workflows

The Cognita (RAG Framework) MCP Server exposes 7 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 Cognita (RAG Framework) to OpenAI Agents SDK via MCP

Follow these steps to integrate the Cognita (RAG Framework) 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 7 tools from Cognita (RAG Framework)

Why Use OpenAI Agents SDK with the Cognita (RAG Framework) MCP Server

OpenAI Agents SDK provides unique advantages when paired with Cognita (RAG Framework) 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

Cognita (RAG Framework) + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Cognita (RAG Framework) MCP Server delivers measurable value.

Automated workflows: build agents that query Cognita (RAG Framework), process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents — one queries Cognita (RAG Framework), another analyzes results, a third generates reports

Data enrichment pipelines: stream data through Cognita (RAG Framework) tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query Cognita (RAG Framework) to resolve tickets, look up records, and update statuses without human intervention

Cognita (RAG Framework) MCP Tools for OpenAI Agents SDK (7)

These 7 tools become available when you connect Cognita (RAG Framework) to OpenAI Agents SDK via MCP:

get_collection

Retrieve explicit Cloud logging tracing explicit Payload IDs

ingest_data

Provision a highly-available JSON Payload generating new Resource directories

list_collections

Identify bounded routing spaces inside the Headless Cognita RAG limit

list_data_sources

Perform structural extraction of properties driving active Buckets

list_models

Inspect deep internal arrays mitigating specific Picture constraints

rag_query

Identify precise active arrays spanning rented Transformation vectors

search_chunks

Enumerate explicitly attached structured rules exporting active Presets

Example Prompts for Cognita (RAG Framework) in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Cognita (RAG Framework) immediately.

"List all RAG collections in Cognita"

"Query collection 'technical-docs' for: 'How do I configure OAuth in our API?'"

"Ingest data from source 'gh-repo-vinkius' into collection 'technical-docs'"

Troubleshooting Cognita (RAG Framework) MCP Server with OpenAI Agents SDK

Common issues when connecting Cognita (RAG Framework) 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.

Cognita (RAG Framework) + OpenAI Agents SDK FAQ

Common questions about integrating Cognita (RAG Framework) 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.