Pydantic AISDK

DBeaver (CloudBeaver) MCP Server

Bring Sql
to Pydantic AI

Name: DBeaver (CloudBeaver) MCP Server
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

Learn how to connect DBeaver (CloudBeaver) to Pydantic AI and start using 19 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.

GDPR Free for Subscribers

Add Connections AccessAuth LoginConfigure ServerCreate TeamCreate UserData Transfer Available Stream ProcessorsData Transfer Export Data From ContainerData Transfer Export Data From ResultsDb Sm TerminateDelete TeamDelete UserGet Active Product LicenseGet Active UserGet Admin User InfoGet Ai SettingsGet All Product LicensesGet Auth ProvidersGet Connection InfoGet Driver List

Unlock for AI Agents

Ask AI about this MCP Server ChatGPT Claude Perplexity

Compatible with every major AI agent and IDE

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

+ other MCP clients

What is the DBeaver (CloudBeaver) MCP Server?

Connect your CloudBeaver (DBeaver Cloud) instance to any AI agent to streamline database administration and server management through natural language.

What you can do

User & Team Management — Create, delete, and inspect user accounts and teams for granular access control using create_user and create_team.
Connection Insights — Fetch detailed configuration and status for specific database connections across projects with get_connection_info.
Driver & Export Discovery — List supported database drivers and available data transfer formats (CSV, JSON, XLSX) via get_driver_list and data_transfer_available_stream_processors.
Server Health & Licensing — Monitor active product licenses, server settings, and AI assistant configurations with get_active_product_license and get_ai_settings.
Authentication Control — Query available auth providers and manage session logins via get_auth_providers and auth_login.

How it works

Subscribe to this server
Provide your CloudBeaver Server URL and API Token
Start managing your database infrastructure from Claude, Cursor, or any MCP client

Who is this for?

Database Administrators — quickly audit user permissions and connection statuses without the web UI
DevOps Engineers — automate user provisioning and verify server configurations
Data Engineers — check available drivers and export capabilities for data pipelines

Built-in capabilities (19)

add_connections_access

Grants users or teams access to specific connections

auth_login

Authenticates a session using a provider and credentials

configure_server

Updates the main server configuration

create_team

Creates a new team for access management

create_user

Creates a new user account (Admin only)

data_transfer_available_stream_processors

Lists available export formats (CSV, JSON, XLSX, etc.)

data_transfer_export_data_from_container

Starts an async task to export data from a table/schema

data_transfer_export_data_from_results

Exports data from a specific SQL query result set

db_sm_terminate

Terminates active database sessions for a connection

delete_team

Removes a team

delete_user

Removes a user account

get_active_product_license

Returns details of the active server license

get_active_user

Returns information about the currently authorized user

get_admin_user_info

Returns detailed admin-level info for a specific user

get_ai_settings

Returns global AI assistant configurations

get_all_product_licenses

Lists all licenses installed on the server

get_auth_providers

Lists all available authentication providers (local, SAML, etc.)

get_connection_info

Returns configuration and status for a specific database connection

get_driver_list

Lists all database drivers supported by the server

Why Pydantic AI?

Pydantic AI validates every DBeaver (CloudBeaver) tool response against typed schemas, catching data inconsistencies at build time. Connect 19 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

—
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
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Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your DBeaver (CloudBeaver) integration code
—
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
—
Dependency injection system cleanly separates your DBeaver (CloudBeaver) connection logic from agent behavior for testable, maintainable code

See it in action

DBeaver (CloudBeaver) in Pydantic AI

AI Agent→Vinkius

High Security·Kill Switch·Plug and Play

Why Vinkius

DBeaver (CloudBeaver) and 4,000+ other MCP servers. One platform. One governance layer.

Teams that connect DBeaver (CloudBeaver) to Pydantic AI 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.

4,000+MCP Servers ready

<40msCold start

60%Token savings

	Raw MCP	Vinkius
Server catalog	Find and host yourself	4,000+ 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

Unlock for AI Agents View step-by-step setup guide for Pydantic AI →

Enterprise Security

Why teams choose Vinkius for DBeaver (CloudBeaver) in Pydantic AI

The DBeaver (CloudBeaver) 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 19 tools execute in hardened sandboxes optimized for native MCP execution.

Your AI agents in Pydantic AI 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.

Unlock for AI Agents View full DBeaver (CloudBeaver) details →

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<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

The Vinkius Advantage

How Vinkius secures
DBeaver (CloudBeaver) for Pydantic AI

Every tool call from Pydantic AI to the DBeaver (CloudBeaver) MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.

< 40msCold start

Ed25519Signed audit chain

60%Token savings

FAQ

Frequently asked questions

How can I see which database types are supported by my CloudBeaver server?

You can use the get_driver_list tool. It returns a comprehensive list of all database drivers installed and supported by your server instance.

Can I check if a specific database connection is active and properly configured?

Yes! Use the get_connection_info tool by providing the Project ID and Connection ID. It will return the current status and configuration details for that specific database.

What file formats are available for exporting data from my databases?

Run the data_transfer_available_stream_processors tool. It lists all available export formats like CSV, JSON, and XLSX supported by your CloudBeaver environment.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your DBeaver (CloudBeaver) MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.