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 Google ADK 7 tools — connect in under 2 minutes

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

google.github.io/adk-docs/tools/mcp-tools

Built by Vinkius GDPR 7 Tools SDK

Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Cognita (RAG Framework) as an MCP tool provider through the Vinkius and your ADK agents can call every tool with full schema introspection.

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

from google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import (
    StreamableHTTPConnectionParams,
)

# Your Vinkius token — get it at cloud.vinkius.com
mcp_tools = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    )
)

agent = Agent(
    model="gemini-2.5-pro",
    name="cognita_rag_framework_agent",
    instruction=(
        "You help users interact with Cognita (RAG Framework) "
        "using 7 available tools."
    ),
    tools=[mcp_tools],
)

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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 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.

Google ADK natively supports Cognita (RAG Framework) as an MCP tool provider — declare the Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 7 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.

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 Google ADK 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 Google ADK via MCP

Follow these steps to integrate the Cognita (RAG Framework) MCP Server with Google ADK.

Install Google ADK

Run pip install google-adk

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Create the agent

Save the code above and integrate into your ADK workflow

Explore tools

The agent will discover 7 tools from Cognita (RAG Framework) via MCP

Why Use Google ADK with the Cognita (RAG Framework) MCP Server

Google ADK provides unique advantages when paired with Cognita (RAG Framework) through the Model Context Protocol.

Google ADK natively supports MCP tool servers — declare a tool provider and the framework handles discovery, validation, and execution

Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with Cognita (RAG Framework)

Production-ready features like session management, evaluation, and deployment come built-in — not bolted on

Seamless integration with Google Cloud services means you can combine Cognita (RAG Framework) tools with BigQuery, Vertex AI, and Cloud Functions

Cognita (RAG Framework) + Google ADK Use Cases

Practical scenarios where Google ADK combined with the Cognita (RAG Framework) MCP Server delivers measurable value.

Enterprise data agents: ADK agents query Cognita (RAG Framework) and cross-reference results with internal databases for comprehensive analysis

Multi-modal workflows: combine Cognita (RAG Framework) tool responses with Gemini's vision and language capabilities in a single agent

Automated compliance checks: schedule ADK agents to query Cognita (RAG Framework) regularly and flag policy violations or configuration drift

Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including Cognita (RAG Framework)

Cognita (RAG Framework) MCP Tools for Google ADK (7)

These 7 tools become available when you connect Cognita (RAG Framework) to Google ADK 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 Google ADK

Ready-to-use prompts you can give your Google ADK 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 Google ADK

Common issues when connecting Cognita (RAG Framework) to Google ADK through the Vinkius, and how to resolve them.

McpToolset not found

Update: pip install --upgrade google-adk

Cognita (RAG Framework) + Google ADK FAQ

Common questions about integrating Cognita (RAG Framework) MCP Server with Google ADK.

How does Google ADK connect to MCP servers?

Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.

Can ADK agents use multiple MCP servers?

Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.

Which Gemini models work best with MCP tools?

Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.