How does this MCP handle different API types?

The MCP uses CData logic to map various API structures into a unified SQL schema that your agent can understand.

Do I need to write Python code to get data from an API?

No. You can use standard SQL queries to interact with the APIs through this MCP.

Can I test if a connection is working?

Yes, you can use the cdata_test_connection capability to ping the proxy and verify the connection is active.

Is it possible to create new connections through the AI client?

Yes, the cdata_create_connection capability allows you to configure new backend data source proxies programmatically.

How are different data groups managed?

The MCP uses virtual workspaces to segment and organize different organizational data groups.

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.

An astronaut overseeing a futuristic data hub

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Connect Cdata Connect Cloud to ChatGPT, Claude and Gemini

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Turn any API into a queryable SQL database for your agent.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

Waiting for input…

Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 8 capabilities

We ship only the actions that matter.

Capability set01 / 02

01-04

4 capabilities in this set.

Part of 8 available through CData Connect.

01
Cdata create connection
This capability sets up a new backend data source proxy using CData logic.
02
Cdata get schema metadata
This capability retrieves the complete backend graph to show all available interaction limits.
03
Cdata execute query
This capability runs SQL queries that route directly into the downstream database to parse values.
04
Cdata get table columns
This capability explores specific schema fields and their definitions within a table boundary.

Capability set02 / 02

05-08

4 capabilities in this set.

Part of 8 available through CData Connect.

05
Cdata list connections
This capability returns the full list of external data sources currently routed through the MCP.
06
Cdata list tables
This capability unpacks the structural collections mapped through your active backend connection.
07
Cdata list workspaces
This capability lists all virtual workspaces used to segment your organizational data groups.
08
Cdata test connection
This capability pings the connected proxy to verify the logical connection is active.

Real work

What teams actually run

Unified Data Auditing

Query multiple different SaaS platforms using a single SQL command to check for data consistency.

Automated Schema Mapping

Use your agent to automatically discover and map new API endpoints into usable database tables.

Rapid Prototyping

Quickly test how data from a new API looks by treating it as a database through the proxy.

Telemetry Data Extraction

Pull specific performance metrics from remote services by routing SQL queries through the gateway.

Automate a task

Put CData Connect to work on one thing.

Step-by-step automations your AI runs through this Connector: the workflow, the prompts to start with, and the exact capabilities behind each move.

One connector, every AI

CData Connect works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

Building your own app? The connector is yours to use.

You don't need a client to put CData Connect to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

835ms average. Fast in production.

CData Connect is checked daily against the live service.

Daily averagePeak 929ms

Oct 3Today

Fastest day: 674ms
Slowest day: 929ms
14-day trend: Improving-6%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 8 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of CData Connect, so you can see the experience inside your AI.

It does not authenticate your account with CData Connect. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

CData Connect Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_SBYp4YpOhOkod1f5osCBPGeYZMDXyp0rzOXZLCrf/mcp

Claude Desktop

Follow the steps below to connect in seconds.

1In Claude Desktop, open Settings → Connectors.
2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
3Click Add and start a new chat — CData Connect capabilities are ready to use.

Configuration · claude_desktop_config.jsonCopy

{
  "mcpServers": {
    "cdata-connect-cloud-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_SBYp4YpOhOkod1f5osCBPGeYZMDXyp0rzOXZLCrf/mcp"
    }
  }
}

Claude
ChatGPT
Cursor
VS Code
Windsurf
Claude Code
JetBrains
Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up CData Connect in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work CData Connect owners hand off.

This MCP is built for technical professionals who need to bridge the gap between structured SQL workflows and unstructured API ecosystems.

01
Data Engineers
They use the MCP to pull unified data matrices from various sources into their pipelines.
02
API Architects
They leverage the gateway to create standardized access layers for complex service meshes.
03
Integration Platform Leads
They use the capability to manage and secure data extraction across multiple organizational endpoints.

FAQ

Questions CData Connect owners ask.

01
How does this MCP handle different API types?
The MCP uses CData logic to map various API structures into a unified SQL schema that your agent can understand.
02
Do I need to write Python code to get data from an API?
No. You can use standard SQL queries to interact with the APIs through this MCP.
03
Can I test if a connection is working?
Yes, you can use the cdata_test_connection capability to ping the proxy and verify the connection is active.
04
Is it possible to create new connections through the AI client?
Yes, the cdata_create_connection capability allows you to configure new backend data source proxies programmatically.
05
How are different data groups managed?
The MCP uses virtual workspaces to segment and organize different organizational data groups.
06
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.
07
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.
08
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.

Explore

More in Developer Tools

Connect CData Connect to Claude, Cursor, ChatGPT & more

Your AI does the work. We keep it safe and sound.

Each Connector runs inside its own sealed environment.

One switch stops every agent. Instantly.

Spending limits that pause instead of surprise.

We ship only the actions that matter.

01-04

Cdata create connection

Cdata get schema metadata

Cdata execute query

Cdata get table columns

05-08

Cdata list connections

Cdata list tables

Cdata list workspaces

Cdata test connection

What teams actually run

Unified Data Auditing

Automated Schema Mapping

Rapid Prototyping

Telemetry Data Extraction

Building your own app? The connector is yours to use.

CData Connect Connector

Claude Desktop

Data Engineers

API Architects

Integration Platform Leads

How does this MCP handle different API types?

Do I need to write Python code to get data from an API?

Can I test if a connection is working?

Is it possible to create new connections through the AI client?

How are different data groups managed?

Can I explicitly route backend programmatic SQL queries through the native CData integration matrix?

How do I explicitly explore active table schema matrix bindings natively?

What orchestrates the proxy connection pings natively mapped transparently?

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