API Design Prover MCP for AI. Validate API Contracts Before Writing a Line of Code.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Connect to your AI in seconds.
API Design Prover validates an API's entire contract before a single line of code is written. This MCP forces semantic HTTP verbs, explicit versioning strategies, and consistent response envelopes across every endpoint.
It catches common design flaws like unbounded lists or mixed data shapes, guaranteeing that the resulting integration will be stable.
What your AI can do
Validate api design
Runs a thorough check on an entire API design, forcing adherence to semantic HTTP verbs, explicit versioning policies, consistent response envelopes, bounded pagination, and structured error contracts.
It validates that each HTTP method (GET, POST, PUT, etc.) is used according to its technical purpose—for instance, only GET can be read-only and idempotent.
The tool forces you to define how API versions are handled (URL paths or headers) and establishes a clear deprecation policy.
It ensures every endpoint—whether listing data, creating a record, or reporting an error—returns the exact same JSON structure.
It prevents endpoints from returning massive, unbounded datasets by requiring explicit pagination limits and cursors.
The tool requires that all failures follow a standardized, machine-readable error contract (RFC 7807), eliminating vague status codes.
Ask an AI about this
Waiting for input…
API Design Prover: 1 Tool Available
This single tool allows users to run a comprehensive validation check against an entire API surface area, enforcing industry-standard contracts.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using API Design Prover on VinkiusValidate Api Design
Runs a thorough check on an entire API design, forcing adherence to semantic HTTP verbs, explicit versioning policies, consistent response...
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Claude AI
Open Claude Settings
Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.
Add Custom Connector
Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:
https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp
Replace [YOUR_TOKEN_HERE] with your token
from cloud.vinkius.com. For OAuth-protected servers, expand
Advanced settings to add credentials.
Start a conversation
Open a new chat. The API Design Prover integration is available immediately — no restart needed.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with API Design Prover, then connect any of our 5,100+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,100+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by API Design Prover. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
VINKIUS INFRASTRUCTURE
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on every call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This connection provides 1 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
API contracts are messy; keeping track of them manually is impossible.
Today, an architect spends days just tracking API documentation. They cross-reference endpoint specs to see if the list endpoints return raw arrays, or if some use nested objects for user details. They check versioning policies across dozens of services and try to map out which verbs are used inconsistently—GET when POST should be used.
With this MCP, you skip that whole review process. You feed the API design into the tool, and it immediately provides a verdict on every required standard. It’s not just checking for errors; it's enforcing an entire architectural contract across five critical dimensions.
API Design Prover MCP delivers provable reliability.
The tedious manual steps of verifying idempotency, confirming the response envelope structure for every single path, or tracking a deprecation cycle across multiple teams all vanish. The tool handles that structural audit in minutes.
It moves API design from an 'art' guided by consensus to an engineering discipline governed by measurable contracts. You get confidence, not just documentation.
What your AI can actually do with this
Building APIs means making promises about how they work. Most AI-generated designs skip crucial steps: they use GET for creation requests; they don't version endpoints; and error messages look nothing alike across different routes. This MCP fixes that problem right at the design stage. It forces you to define every contract—how data looks on success, what happens when it fails, and how pagination works—before your team writes a single test case.
You won't get vague suggestions about 'best practices.' Instead, you get an actionable verdict: Is this API ready? If not, the tool tells you exactly which protocol violation needs fixing, guiding you toward Stripe-grade reliability. When you connect to it via Vinkius, it acts as a strict gatekeeper for your entire service catalog.
019e599b-20d1-7204-8c04-16dd92af2de7 
Here's how it actually works
The bottom line is that it turns abstract design ideas into concrete, verifiable technical specifications.
Provide the intended API surface and its functional requirements to your agent.
The MCP runs a series of five decision pivots, checking for verb semantics, versioning plans, response consistency, pagination bounds, and error contracts.
You receive a definitive verdict: either 'API_PROVEN' with all best practices met, or a specific violation report detailing exactly what needs correction.
Who is this actually for?
This MCP is built for senior platform engineers and architects. Use it when you're tired of debugging integration failures caused by vague API contracts; the kind of failure that only surfaces after months of usage.
Designs the core service boundaries, ensuring every new endpoint adheres to enterprise-grade standards before it hits staging.
Needs a way to validate complex API designs quickly, catching issues like mixed data types or incorrect HTTP verb usage without writing boilerplate tests.
Validates the technical feasibility of a new feature by ensuring that the underlying API contracts are consistent and versionable for future development cycles.
What Changes When You Connect
Prevents 'Verb Abuse' (e.g., using GET for creation). The tool forces semantic verbs, guaranteeing that your endpoints behave predictably across caching layers and proxies.
Eliminates the risk of breaking changes. By enforcing versioning strategies, you can plan deprecation timelines years out, giving consumers time to migrate.
Guarantees consistent client parsing. It forces a unified JSON envelope for every single endpoint—success, failure, or list—so your SDKs never break due to shape chaos.
Stops memory leaks and timeouts. The tool mandates pagination bounds, ensuring that listing endpoints can't return 100K records in one call.
Makes error handling reliable. Instead of generic 'Internal Server Error' messages, the MCP forces structured, machine-readable error contracts (RFC 7807).
Saves review time. Architects use this to run a single contract validation pass instead of spending days manually checking documentation against implementation.
See it in action
Migrating an old monolithic API
The team is porting 50 endpoints from an old service. Instead of testing each one individually, the architect runs validate_api_design on the entire surface area. The tool instantly highlights which routes need version prefixes and which data types are inconsistent across the whole suite.
Adding a new resource type
A developer needs to add 'Invoices' endpoints. They prompt their agent, detailing POST/GET verbs and response shapes. The tool immediately flags that they used GET for creation, forcing them to switch to the proper POST verb mapping.
Debugging client integration failures
The QA team finds a sporadic bug where the mobile app crashes when fetching large user lists. Running validate_api_design reveals that pagination is unbounded, confirming the root cause and enforcing necessary limits.
The honest tradeoffs
Relying on simple endpoint documentation
A developer writes down 'GET /users' returns a list of users. Later, they realize some endpoints return raw arrays while others use wrapped objects for consistency.
You must run validate_api_design. It enforces responseConsistent, demanding that every single endpoint uses the same JSON envelope structure, making client parsing reliable.
Using temporary endpoints
The team implements a 'beta' endpoint without any plan for deprecation or versioning. The first schema change breaks all integrated services.
Always run validate_api_design and ensure the resulting verdict passes versioningDefined. This forces an explicit, long-term deprecation timeline.
Ignoring error contracts
The API returns a 500 status code with just a generic string message ('Something went wrong'). The frontend has no way to display specific user feedback.
Use validate_api_design and ensure the contract is passed for errorContracted. This mandates structured, machine-readable error formats.
When It Fits, When It Doesn't
Use this MCP if your primary concern is the contract between services. If you're building an API surface that needs to last years, this tool is mandatory; it enforces architectural rigor and contract stability. Don't use it if all you need is to validate basic business logic (e.g., 'Does user A have access to resource B?'). For those tasks, a simple function call is enough. If your goal is simply data transformation or calling external APIs without defining the core service structure, look for dedicated workflow tools instead.
Questions you might have
How does the API Design Prover MCP handle different data types? +
The tool forces response consistency, meaning every endpoint must return the same structure regardless of whether it's listing resources or detailing one. This prevents client-side parsing errors.
Does validate_api_design check business logic? +
No. It only validates how your API is structured—the contracts, verbs, and formats. Business logic validation requires separate unit or integration tests.
What does the MCP do if I don't define a versioning strategy? +
The tool will fail the versioningDefined pivot immediately. It forces you to specify whether versions change via URL paths, headers, or query params, ensuring future compatibility.
Can validate_api_design help with pagination limits? +
Yes. The tool mandates that list endpoints must enforce bounds (limit/offset or cursor) and cannot return unlimited rows, preventing memory leaks on the client side.
How does running validate_api_design help define authentication requirements for my endpoints? +
It doesn't enforce the auth mechanism, but it forces you to treat security as a contract requirement. You must specify which authenticated roles or scopes are required for read (GET) versus write (POST/PUT) actions.
Does validate_api_design check if I need rate limiting or performance boundaries? +
Yes, it validates that your contract includes usage limits. You must define hard server-side bounds and recommend appropriate throttling headers (like X-RateLimit) to prevent service overload.
When I use validate_api_design, does the error contract cover tracing and specific failure codes? +
Absolutely. The tool mandates adherence to RFC 7807 Problem Details. This requires more than a simple message; it demands structured fields like type, status code, and a unique correlation ID for debugging.
If I update an endpoint, how does validate_api_design help manage the transition or deprecation period? +
It forces you to define a formal deprecation policy. When changing a field or removing an endpoint, the MCP requires specifying the sunset timeline and providing migration guidance for existing consumers.
Why does API Design Prover require RFC 7807? +
RFC 7807 (Problem Details) is the industry standard for HTTP API error shapes. It ensures that regardless of the endpoint or technology, client developers receive errors they can easily parse and handle.
What versioning methods are supported? +
Path versioning (e.g., /v1/users), media type/header versioning, or query parameters. Path versioning is highly recommended due to its simple implementation and client compatibility.
Does it enforce GraphQL standards? +
This tool is focused on REST APIs and HTTP resource design. For GraphQL or gRPC, you can adapt the pivots, but out-of-the-box checks validate HTTP status, HTTP verbs, and REST envelope consistency.
We've already built the connector for API Design Prover. Just plug in your AI agents and start using Vinkius.
No hosting. No infrastructure. No complex setup.
All 1 tools are live and waiting.
You're up and running in seconds.
Gemini Vinkius gives your AI agents access to the full catalog of app connectors, all fully managed, secure, and enterprise-ready. One subscription, every tool you need.
Built, hosted, and secured by Vinkius. You just connect and go.