CData Connect Cloud Connector for AI agents.
8 live capabilities
Query and map diverse API data sources using standard SQL.
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Why people use CData Connect Cloud
CData Connect Cloud SQL Mapping for Data Engineers
CData Connect Cloud fixes this by creating a universal bridge. It takes those disparate sources and maps them into a standard schema that your AI agent can query directly. You stop writing wrappers and start running SQL. It turns a week of integration work into a few minutes of configuration.
What Vinkius changes
You get a single way to talk to any data source using standard SQL.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 6,100+ Connectors
- Real-world use case 01
The Messy API Problem
A data engineer needs to pull customer info from three different SaaS capabilities.
- Real-world use case 02
Rapid Schema Discovery
An analyst wants to know what's in a new database.
- Real-world use case 03
Automated Connection Auditing
An IT lead needs to see every active integration.
Complete set · 8capabilities
The complete CData Connect Cloud capability set.
These are the exact actions your AI can choose when you ask it to work with CData Connect Cloud.
01—04
4 capabilities in this set.
Part of 8 available through CData Connect Cloud.
- 01 Capability
Cdata list connections
Use cdata_list_connections to see every data source currently connected to your gateway. Use this to audit your active integrations.
- 02 Capability
Cdata list tables
Use cdata_list_tables to see all the tables available in a specific connection. It maps out the structural collections for you.
- 03 Capability
Cdata list workspaces
Use cdata_list_workspaces to see all the different logical data groups in your account. This helps segment your data by department or project.
- 04 Capability
Cdata create connection
Use cdata_create_connection to configure a new backend data source proxy. This lets you add new sources to your gateway instantly.
05—08
4 capabilities in this set.
Part of 8 available through CData Connect Cloud.
- 05 Capability
Cdata execute query
Run cdata_execute_query to run SQL queries against your connected data sources. It handles the translation to the underlying API for you.
- 06 Capability
Cdata get schema metadata
Use cdata_get_schema_metadata to see the full structure of a connected backend. It shows every interaction limit and field mapped natively.
- 07 Capability
Cdata get table columns
Use cdata_get_table_columns to get the exact fields for a specific table. This helps your agent know exactly what data it can pull.
- 08 Capability
Cdata test connection
Use cdata_test_connection to check if your connection to a data source is still active. It pings the proxy to check the link is live.
Set up in minutes
One URL. Then ask CData Connect Cloud to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use CData Connect Cloud 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_SBYp4YpOhOkod1f5osCBPGeYZMDXyp0rzOXZLCrf/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 CData Connect Cloud, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable CData Connect Cloud for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_SBYp4YpOhOkod1f5osCBPGeYZMDXyp0rzOXZLCrf/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 CData Connect Cloud URL.
- Step 03
Save and start
Save the connection and enable CData Connect Cloud in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"cdata-connect-cloud": {
"url": "https://edge.vinkius.com/vk_preview_SBYp4YpOhOkod1f5osCBPGeYZMDXyp0rzOXZLCrf/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 CData Connect Cloud
Open Agent mode in chat and ask: "Using CData Connect Cloud, help me...". 8 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"cdata-connect-cloud": {
"url": "https://edge.vinkius.com/vk_preview_SBYp4YpOhOkod1f5osCBPGeYZMDXyp0rzOXZLCrf/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 CData Connect Cloud
Ask Copilot: "Using CData Connect Cloud, help me...". 8 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"cdata-connect-cloud": {
"url": "https://edge.vinkius.com/vk_preview_SBYp4YpOhOkod1f5osCBPGeYZMDXyp0rzOXZLCrf/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 CData Connect Cloud
Open Cascade and ask: "Using CData Connect Cloud, help me...". 8 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"cdata-connect-cloud": {
"url": "https://edge.vinkius.com/vk_preview_SBYp4YpOhOkod1f5osCBPGeYZMDXyp0rzOXZLCrf/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 CData Connect Cloud
Ask Cline: "Using CData Connect Cloud, help me...". 8 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add cdata-connect-cloud --transport http "https://edge.vinkius.com/vk_preview_SBYp4YpOhOkod1f5osCBPGeYZMDXyp0rzOXZLCrf/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 CData Connect Cloud
Ask Claude: "Using CData Connect Cloud, show me...". 8 tools are ready
Where the request belongs
Work CData Connect can move forward.
This is for the data engineer who's tired of writing glue code for every new API. It's for the architect who needs to centralize dozens of messy data streams into one manageable hub.
Data Engineer
Building pipelines that need to hit multiple APIs without writing fifty different wrappers.
API Architect
Designing a unified data layer that lets other teams query anything via a single gateway.
Integration Lead
Managing complex data migrations where mapping schemas across different systems is the main bottleneck.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
Browse ConnectorsDirectus
Turn any SQL database into a powerful headless CMS with instant REST and GraphQL APIs for your custom content models.
Fivetran
Manage data movement via Fivetran. monitor connectors and destinations, handle groups, track sync states, and audit users directly from any AI agent.
ElectricSQL (Sync Engine)
Sync Postgres data to your AI agent in real-time using ElectricSQL's HTTP Sync API. fetch shapes, stream updates, and query subsets.
Sigma Computing
Equip your AI agent to audaciously navigate your Sigma data workflows. List core workbooks, map connections, trace dataset lineage, and monitor organization teams directly from your IDE.
Retable
Organize data in smart spreadsheets with relational views, team collaboration, and workflow automation that goes beyond basic tables.
Ninox
Build custom business databases and apps with a visual platform that replaces spreadsheets with structured, relational data.
Bring your own AI
Change the model, client or framework. Keep CData Connect 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 CData Connect.
The practical details behind the request, access and result.
What is CData Connect Cloud MCP?
It's a universal data gateway that lets your AI agent talk to various APIs and databases using standard SQL. It maps messy external data into a clean format your agent can easily read.
Can I use it to query APIs with SQL?
Yes. The Connector translates your SQL queries into the correct API calls automatically, so you don't have to worry about the underlying technical details.
Does CData Connect Cloud support multiple data sources?
Yes, it handles many different types of data sources at once. You can connect to various APIs and databases and treat them all as part of one unified data library.
How do I secure my credentials with CData Connect Cloud?
You can securely pass your credentials like usernames and auth tokens to your agent. This keeps your keys out of your prompts while still allowing the agent to access the data.
Can my AI agent explore my database schemas?
Yes, your agent can use the Connector to look at your tables and columns. This helps it understand what data is available before it tries to run any specific queries for you.
Is CData Connect Cloud good for data engineers?
It's built specifically for data engineers and architects. It removes the need to write repetitive glue code for every new API integration you have to perform.
Can I explicitly route backend programmatic SQL queries through the native CData integration matrix?
Yes! Utilize execute_query providing explicit logic passing straight structural limits resolving downstream implicitly.
How do I explicitly explore active table schema matrix bindings natively?
Target explicit limit matrices completely calling list_tables bounding safely native UUID mappings retrieving exactly proxy schemas natively secure.
What orchestrates the proxy connection pings natively mapped transparently?
Yes, native traces executing explicitly under test_connection resolve infrastructure matrix logic health verifying data clusters inherently completely mapped.
One connection away
Give your agent a direct line to CData Connect.
Connect CData Connect once. Keep it beside 6,100+ managed Connectors when the next task needs more.
Explore every Connector No credit card required · Free tier available