Can my AI agent trigger an immediate document processing job?

Yes! If you have a workflow configured to pull files from an S3 bucket and load them into a Pinecone index, you can ask your agent to `trigger workflow XYZ`. It will start the execution and return the new Job ID, which you can use to track the progress.

How can I verify if my RAG pipelines are failing or succeeding?

Ask your agent to list your workflow jobs. It will securely connect to Unstructured's engine and return historical and active executions, displaying statuses such as 'completed', 'failed', or 'in_progress'. This is extremely useful for MLOps engineers diagnosing ingestion alerts directly in their terminal.

Can I edit the destination database directly through the agent?

This server is focused on auditing and executing your existing pipelines. Currently, you can list all connections (sources and destinations) and obtain their details, but creating or destructively modifying vector database connectors must be done inside the Unstructured dashboard for security.

Unstructured MCP Server for Google ADK 6 tools — connect in under 2 minutes

Name: Unstructured
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 6 Tools SDK

Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Unstructured 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

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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="unstructured_agent",
    instruction=(
        "You help users interact with Unstructured "
        "using 6 available tools."
    ),
    tools=[mcp_tools],
)

Fully ManagedVinkius Servers

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EU AI ActCompliant

DLPData protection

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<40msKill switch

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 Unstructured MCP Server

Connect your Unstructured.io account to any AI agent to automate data ingestion and document processing pipelines seamlessly. Transform complex files into clean, AI-ready data without leaving your workflow.

Google ADK natively supports Unstructured as an MCP tool provider — declare the Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 6 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

Data Sources — List all configured remote data connectors (e.g. S3, GCS, SharePoint) to see where documents can be pulled from.
Data Destinations — Browse target locations (like Vector DBs or SQL databases) where structured output is sent.
Processing Workflows — List end-to-end pipelines, retrieve specific workflow configurations, and explore source-destination mappings.
Job Execution — Manually trigger immediate document ingestion and partitioning jobs, and track their execution IDs.
Job Monitoring — List active and historical workflow execution jobs to monitor the progress of your document processing tasks.

The Unstructured MCP Server exposes 6 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 Unstructured to Google ADK via MCP

Follow these steps to integrate the Unstructured 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 6 tools from Unstructured via MCP

Why Use Google ADK with the Unstructured MCP Server

Google ADK provides unique advantages when paired with Unstructured 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 Unstructured

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 Unstructured tools with BigQuery, Vertex AI, and Cloud Functions

Unstructured + Google ADK Use Cases

Practical scenarios where Google ADK combined with the Unstructured MCP Server delivers measurable value.

Enterprise data agents: ADK agents query Unstructured and cross-reference results with internal databases for comprehensive analysis

Multi-modal workflows: combine Unstructured tool responses with Gemini's vision and language capabilities in a single agent

Automated compliance checks: schedule ADK agents to query Unstructured regularly and flag policy violations or configuration drift

Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including Unstructured

Unstructured MCP Tools for Google ADK (6)

These 6 tools become available when you connect Unstructured to Google ADK via MCP:

get_workflow_details

Retrieves configuration details for a specific processing workflow

list_data_destinations

g. Vector DBs, SQL). Lists all configured target locations for processed data

list_data_sources

Lists all configured remote data connectors (e.g. S3, GCS)

list_processing_workflows

Lists all end-to-end document processing pipelines

list_workflow_jobs

Lists all active and historical workflow execution jobs

trigger_workflow_execution

Returns a job ID. Manually triggers an immediate execution of a processing workflow

Example Prompts for Unstructured in Google ADK

Ready-to-use prompts you can give your Google ADK agent to start working with Unstructured immediately.

"Show me all our active destination connectors."

"List the historical processing jobs from today."

"Trigger the engineering onboarding workflow."

Troubleshooting Unstructured MCP Server with Google ADK

Common issues when connecting Unstructured to Google ADK through the Vinkius, and how to resolve them.

McpToolset not found

Update: pip install --upgrade google-adk

Unstructured + Google ADK FAQ

Common questions about integrating Unstructured 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.