Databox Connector for AI agents.
10 live capabilities
Manage your business intelligence and KPI dashboards with natural language.
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Why people use Databox
Manage Databox KPI Dashboards Without Manual Data Entry
With this Connector, you just tell your agent to do it. It handles the IDs and the records, updating your dashboard instantly. You get a clean workflow where the data just shows up, letting you focus on the insights instead of the upload process.
What Vinkius changes
You get a conversational interface for your entire Databox data pipeline.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 5,900+ Connectors
- Real-world use case 01
Marketing Report Update
A marketing manager asks the agent to push last week's lead counts into the 'Lead Gen' dataset using push_metrics_data.
- Real-world use case 02
Storage Audit
An ops lead asks the agent to check how much storage is left before starting a new data migration using get_storage_statistics.
- Real-world use case 03
New Data Source Setup
A data analyst asks the agent to list existing sources and create a new one for a new CRM integration using list_data_sources.
Complete set · 10capabilities
The complete Databox capability set.
These are the exact actions your AI can choose when you ask it to work with Databox.
01—04
4 capabilities in this set.
Part of 10 available through Databox.
- 01 Capability
List datasets
List all the datasets in your account. This helps you find the right place to push data.
- 02 Capability
Create data source
Create a new data source for your dashboard. This helps you add new integrations quickly.
- 03 Capability
Create dataset
Create a new dataset to hold your records. Use this to organize different types of data.
- 04 Capability
Delete dataset
Remove a dataset you no longer need. This keeps your workspace clean.
05—07
3 capabilities in this set.
Part of 10 available through Databox.
- 05 Capability
Get dataset details
Get specific information about a dataset. Use this to check schemas or IDs.
- 06 Capability
List accounts
See a list of all Databox accounts. This is great for managing multiple organizational profiles.
- 07 Capability
List data sources
See all the data sources for a specific account. Use this to audit your active feeds.
08—10
3 capabilities in this set.
Part of 10 available through Databox.
- 08 Capability
List dataset metrics
See the metrics inside a specific dataset. This helps you understand what data is already there.
- 09 Capability
Push metrics data
Push new data records into a dataset. This is how you update your dashboards in real-time.
- 10 Capability
Validate authentication
Use this to verify credentials before performing other operations. Validate your Databox API key and check authentication status
Set up in minutes
One URL. Then ask Databox to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Databox from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_m5wxPLxA4DZzlEAGQvVBd7mHBeJdKwSaNPtHchcU/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it Databox, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Databox for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_m5wxPLxA4DZzlEAGQvVBd7mHBeJdKwSaNPtHchcU/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the Databox URL.
- Step 03
Save and start
Save the connection and enable Databox in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"databox": {
"url": "https://edge.vinkius.com/vk_preview_m5wxPLxA4DZzlEAGQvVBd7mHBeJdKwSaNPtHchcU/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using Databox
Open Agent mode in chat and ask: "Using Databox, help me...". 10 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"databox": {
"url": "https://edge.vinkius.com/vk_preview_m5wxPLxA4DZzlEAGQvVBd7mHBeJdKwSaNPtHchcU/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using Databox
Ask Copilot: "Using Databox, help me...". 10 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"databox": {
"url": "https://edge.vinkius.com/vk_preview_m5wxPLxA4DZzlEAGQvVBd7mHBeJdKwSaNPtHchcU/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using Databox
Open Cascade and ask: "Using Databox, help me...". 10 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"databox": {
"url": "https://edge.vinkius.com/vk_preview_m5wxPLxA4DZzlEAGQvVBd7mHBeJdKwSaNPtHchcU/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using Databox
Ask Cline: "Using Databox, help me...". 10 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add databox --transport http "https://edge.vinkius.com/vk_preview_m5wxPLxA4DZzlEAGQvVBd7mHBeJdKwSaNPtHchcU/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using Databox
Ask Claude: "Using Databox, show me...". 10 tools are ready
Where the request belongs
Work Databox can move forward.
The data analyst who's tired of manual entry, the marketing lead who needs real-time KPIs without the overhead, and the ops manager who needs to monitor data budgets without digging through logs.
Data Analyst
They use this to verify dataset structures and ingest new data points without writing custom SQL or manual scripts.
Marketing & Sales Ops
They use this to automate reporting for custom metrics and monitor storage limits while staying in their primary workspace.
Operations Lead
They use this to track API activity logs and manage data source connections through quick voice or text queries.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
Browse ConnectorsPlecto
Automate KPI dashboards and data tracking via Plecto. manage registrations, dashboards, and teams directly from any AI agent.
Klipfolio
Build real-time business dashboards that pull from hundreds of data sources and give every stakeholder the metrics they need.
Redash
Connect to Redash to manage SQL queries, execute data visualizations, and monitor dashboards directly from your AI agent.
Mode (Collaborative Data Platform)
Manage collaborative analytics via Mode. list data reports, explore organizational spaces, and audit data sources.
Grid
Turn spreadsheet data into interactive dashboards and visual stories that make numbers accessible to every stakeholder.
Tableau
Access workbooks, views, data sources, and dashboard insights from Tableau. the enterprise BI and analytics platform.
Bring your own AI
Change the model, client or framework. Keep Databox connected.
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Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
JetBrains -
Warp -
Amazon Q -
Antigravity -
BoltAI -
Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about Databox.
The practical details behind the request, access and result.
Can the Databox MCP push data to my dashboards?
Yes, it lets your agent send records directly into your datasets. This means you can update your live dashboards using natural language instead of manual uploads.
How do I check my Databox storage limits with an AI?
You can simply ask your agent to check your stats. It will retrieve your current usage and tell you how much storage you have left in your analytics budget.
Can I manage my Databox datasets using natural language?
Yes, you can create, list, and delete datasets through your AI client. This helps you keep your workspace organized without leaving your workspace.
Is there a way to see my Databox API logs?
Yes, the agent can retrieve your activity logs. This is useful for monitoring your usage and troubleshooting any connection issues.
Can I use this to connect new data sources?
Yes, you can list and create new sources through the agent. It helps you manage your data architecture and ensure your feeds are healthy.
Does this Connector help with KPI tracking?
Absolutely. It streamlines how you ingest and manage the data that feeds your KPIs, making it much faster to keep your team focused on the right metrics.
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 capability. 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 capability allows for immediate ingestion of data records, making them available for visualization in Databox instantly.
One connection away
Give your agent a direct line to Databox.
Connect Databox once. Keep it beside 5,900+ managed Connectors when the next task needs more.
Explore every Connector No credit card required · Free tier available