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Google ADKSDK
Google ADK
OpenAPI Validator Engine MCP Server

Bring Api Specification
to Google ADK

Learn how to connect OpenAPI Validator Engine to Google ADK and start using 1 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.

MCP Inspector GDPR Free for Subscribers
Validate Openapi

Compatible with every major AI agent and IDE

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+ other MCP clients
OpenAPI Validator Engine

What is the OpenAPI Validator Engine MCP Server?

Your agent is about to generate an SDK from an OpenAPI spec. But the spec has a missing $ref, an invalid schema type, and a path parameter that doesn't match the URL template. The generated code compiles but crashes at runtime. Nobody finds it until production.

This MCP validates OpenAPI/Swagger specifications against the official JSON Schema before any code generation happens. It catches every structural error with the exact path where it occurred.

The Superpowers

  • 4 Versions: OpenAPI 2.0 (Swagger), 3.0, 3.1, and 3.2 — auto-detected.
  • Exact Error Paths: Each error includes the JSON pointer (e.g. paths./users.get.responses.200.content) for surgical fixes.
  • Local: No external API calls. The validation schema is embedded.
  • Quality Gate: Use as a CI/CD gate — reject code generation from invalid specs.

Built-in capabilities (1)

validate_openapi

Pass the spec as a JSON string. The engine validates against the official OpenAPI JSON Schemas and returns all errors with paths. Supports Swagger 2.0, OpenAPI 3.0, 3.1, and 3.2. Validates OpenAPI/Swagger specifications (2.0, 3.0.x, 3.1.x, 3.2.x) offline. Returns version, validity, and detailed error list

Why Google ADK?

Google ADK natively supports OpenAPI Validator Engine as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 1 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.

  • Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution

  • Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with OpenAPI Validator Engine

  • Production-ready features like session management, evaluation, and deployment come built-in. not bolted on

  • Seamless integration with Google Cloud services means you can combine OpenAPI Validator Engine tools with BigQuery, Vertex AI, and Cloud Functions

G
See it in action

OpenAPI Validator Engine in Google ADK

AI AgentVinkius
High Security·Kill Switch·Plug and Play
Why Vinkius

OpenAPI Validator Engine and 4,000+ other MCP servers. One platform. One governance layer.

Teams that connect OpenAPI Validator Engine to Google ADK 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 catalogFind and host yourself4,000+ managed
InfrastructureSelf-hostedSandboxed V8 isolates
Credential handlingPlaintext in configVault + runtime injection
Data loss preventionNoneConfigurable DLP policies
Kill switchNoneGlobal instant shutdown
Financial circuit breakersNonePer-server limits + alerts
Audit trailNoneEd25519 signed logs
SIEM log streamingNoneSplunk, Datadog, Webhook
HoneytokensNoneCanary alerts on leak
Custom domainsNot applicableDNS challenge verified
GDPR complianceManual effortAutomated purge + export
Enterprise Security

Why teams choose Vinkius for OpenAPI Validator Engine in Google ADK

The OpenAPI Validator Engine 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 1 tools execute in hardened sandboxes optimized for native MCP execution.

Your AI agents in Google ADK 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.

OpenAPI Validator Engine
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 OpenAPI Validator Engine for Google ADK

Every tool call from Google ADK to the OpenAPI Validator Engine 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

01

Which OpenAPI versions does it support?

Swagger 2.0, OpenAPI 3.0.x, OpenAPI 3.1.x, and OpenAPI 3.2.x. The version is auto-detected from the spec.

02

Does it validate $ref references?

Yes. The validator checks that all $ref pointers resolve to existing schema definitions. Missing or circular references are reported as errors.

03

Can I use this as a CI/CD quality gate?

Absolutely. If isValid is false, block code generation and SDK publishing. The error paths pinpoint exactly what to fix.

04

How does Google ADK connect to MCP servers?

Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.

05

Can ADK agents use multiple MCP servers?

Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.

06

Which Gemini models work best with MCP tools?

Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.

07

McpToolset not found

Update: pip install --upgrade google-adk

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