Bring Multi Model
to Pydantic AI
Learn how to connect SurrealDB to Pydantic AI and start using 16 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the SurrealDB MCP Server?
Connect your SurrealDB database to any AI agent and take full control of your data layer through natural conversation.
What you can do
- SurrealQL Execution — Run raw SurrealQL statements using the
execute_sqltool for complex queries and logic. - Record Management — Create, update, and modify records in specific tables with tools like
create_record,update_record, ormodify_record. - Table Operations — Quickly
select_allordelete_allrecords from a target table to manage your data at scale. - Health Monitoring — Check server status and health metrics using
get_statusandget_healthto ensure uptime. - Data Portability — Use
import_sqlandexport_datato move information in and out of your instance seamlessly.
How it works
- Subscribe to this server
- Enter your SurrealDB URL and credentials (NS, DB, and Auth)
- Start managing your multi-model database from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Backend Developers — test queries and inspect database state without switching windows.
- Data Engineers — perform quick data migrations or schema inspections via natural language.
- Product Managers — query business metrics directly from the database using SurrealQL.
Built-in capabilities (16)
Create a record with a random ID
Create a specific record
Delete all records in a table
Delete a specific record
Can pass variables via URL query parameters. Execute SurrealQL statements
Export data
Check SurrealDB health
Check SurrealDB web server status
Get SurrealDB version
Import SurrealQL queries
Modify all records in a table (Merge)
Modify a specific record (Merge)
Select all records in a table
Select a specific record
Update all records in a table
Update a specific record
Why Pydantic AI?
Pydantic AI validates every SurrealDB tool response against typed schemas, catching data inconsistencies at build time. Connect 16 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
- —
Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your SurrealDB integration code
- —
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
- —
Dependency injection system cleanly separates your SurrealDB connection logic from agent behavior for testable, maintainable code
SurrealDB in Pydantic AI
SurrealDB and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect SurrealDB 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.
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 |
Why teams choose Vinkius for SurrealDB in Pydantic AI
The SurrealDB 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 16 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.
* 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
SurrealDB for Pydantic AI
Every tool call from Pydantic AI to the SurrealDB MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I run custom SurrealQL queries with variables?
Yes! Use the execute_sql tool. You can provide the raw SQL string and an optional JSON object of variables to be used in the query.
How do I check if my SurrealDB instance is online and healthy?
You can use the get_status tool to check the web server status or get_health to verify that both the server and the storage engine are functioning correctly.
Is it possible to delete all records from a specific table at once?
Yes, the delete_all tool allows you to remove all records from a specified table in a single operation.
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 SurrealDB MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.
MCPServerHTTP not found
Update: pip install --upgrade pydantic-ai
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