Bring Kpi Tracking
to Google ADK
Learn how to connect Databox to Google ADK and start using 12 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the Databox MCP Server?
Connect your Databox account to any AI agent and take full control of your business intelligence and data ingestion workflows through natural conversation.
What you can do
- Dataset Orchestration — List and manage your database collections (tables) programmatically, including retrieving detailed schema metadata and primary key configurations
- High-Fidelity Ingestion — Programmatically push arrays of raw data records directly into Databox to coordinate real-time metric visualization and reporting
- Source Architecture — Access and manage your directory of data source integrations and connected accounts to maintain high-fidelity data feeds
- Usage Monitoring — Programmatically track your data storage statistics and API activity logs to coordinate your analytics budget and quotas
- Operational Visibility — Check authenticated user profiles and verify system connectivity directly through your agent for instant BI reporting
How it works
1. Subscribe to this server
2. Retrieve your API Key (v1) from your Databox dashboard (Account Settings > API Tokens)
3. Start pushing your business metrics and managing datasets from Claude, Cursor, or any MCP client
No more manual metric logging or digging through complex SQL transformations in the dashboard. Your AI acts as your dedicated data engineer and BI coordinator.
Who is this for?
- Data Analysts — instantly ingest new data points and verify dataset structures using natural language commands
- Marketing & Sales Ops — automate the reporting of custom metrics and monitor storage limits without leaving your workspace
- Operations Leads — track API activity logs and manage data source connections through simple AI queries
Built-in capabilities (12)
Create a new data source
Create a new dataset
Delete a dataset
Get authenticated user profile
Get details for a specific dataset
Get data storage stats
List all Databox accounts
List API activity logs
List data sources for an account
List metrics in a dataset
List all datasets
Ingest data into a dataset
Why Google ADK?
Google ADK natively supports Databox as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 12 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.
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Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution
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Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with Databox
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Production-ready features like session management, evaluation, and deployment come built-in. not bolted on
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Seamless integration with Google Cloud services means you can combine Databox tools with BigQuery, Vertex AI, and Cloud Functions
Databox in Google ADK
Databox and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Databox to Google ADK through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 3,400+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Databox in Google ADK
The Databox 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. All 12 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Google ADK only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* 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
How Vinkius secures
Databox for Google ADK
Every tool call from Google ADK to the Databox MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How do I find my Databox API Key?
Log in to your account, navigate to Account Settings > API Tokens, and copy your unique v1 API Key.
Can I create new datasets via AI?
Yes! Use the create_dataset tool. You'll need to specify a title, a source ID, and an array of primary keys for the table structure.
Does it support real-time data pushing?
The push_metrics_data tool allows for immediate ingestion of data records, making them available for visualization in Databox instantly.
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.
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Update: pip install --upgrade google-adk