API Design Prover MCP. Validate API contracts before you commit a line of code.
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API Design Prover validates HTTP API designs before you write code. It enforces semantic HTTP verbs, standardizes versioning strategies, and checks for consistent response envelopes and error contracts.
Use it to ensure your API contracts are structured, paginated, and error-handled properly, preventing client-side breakage before deployment.
What your AI agents can do
Validate api design
Checks your entire API design, ensuring correct HTTP verbs, versioning, response envelopes, pagination, and error contracts are all defined.
It checks that each endpoint uses the correct HTTP verb (GET, POST, PUT, etc.) based on whether the operation is read-only, creates a resource, or updates a field.
It validates that the API design includes a defined versioning strategy, such as a URL path prefix (/v1/) or a dedicated HTTP header.
It verifies that every endpoint returns data using a unified payload structure, preventing client-side parsing headaches.
It ensures that collection endpoints enforce pagination limits (e.g., limit-offset or cursor-based) and define a strict maximum page size.
It confirms that error payloads follow industry standards like RFC 7807, providing structured codes and diagnostic details instead of raw text.
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API Design Prover MCP Server: 1 Tool
Use the validate_api_design tool to check your API contract for five structural flaws, ensuring it's ready for production use.
019e599bvalidate api design
Checks your entire API design, ensuring correct HTTP verbs, versioning, response envelopes, pagination, and error contracts are all defined.
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What you can do with this MCP connector
Listen up. If you're building an API, you gotta check the design before you write a single line of code. The API Design Prover is the gatekeeper that makes sure your HTTP API contracts are solid. It forces you to define the whole interface—the rules—before you even get to the backend logic.
This keeps you from running into messy, breaking changes later on.
It uses the validate_api_design tool to check your whole API design. This tool verifies that every endpoint uses the right HTTP verb, that you've figured out versioning, and that your response and error contracts are all consistent.
When you use it, you get guarantees on five key things:
- HTTP Verbs: It checks if the endpoint uses the right HTTP verb. You can't use
GETif you're actually creating something, and you can't usePOSTjust to read data. It makes sure the verbs match what the operation is supposed to do. - Versioning: You gotta tell it how you're versioning the API. The Prover validates that you've defined a strategy, whether that's a path prefix like
/v1/or a specific HTTP header. - Response Structure: It makes sure every endpoint returns data in a unified wrapper. This stops your clients from having to write custom parsing logic for every single route.
- Pagination: For collection endpoints, it makes sure you've set strict pagination limits. It checks that you define a maximum page size and use proper methods like cursor-based or limit-offset.
- Error Handling: It confirms that error payloads follow industry standards, like RFC 7807. Instead of getting some raw text or a stack trace, you get structured error codes and details your client can actually program against.
How API Design Prover MCP Works
- 1 Define your API surface (endpoints, verbs, and expected payload shapes).
- 2 Run the design through the
validate_api_designtool. The tool analyzes the contract against five industry standards. - 3 The tool returns a verdict: either
API_PROVEN(clean design) or a specific flaw (e.g.,VERB_ABUSE,SHAPE_INCONSISTENT).
The bottom line is, it forces you to solidify your API contract and fix structural flaws before you write any code.
Who Is API Design Prover MCP For?
API architects, backend engineers, and dev teams that are constantly dealing with inter-service communication. You use this when your API needs to be stable, predictable, and consumable by many clients (internal or external). It’s for the person tired of debugging client-side parsing errors because one microservice changed its response shape.
Uses this to verify that new routes adhere to versioning and use semantic HTTP verbs before implementation.
Uses this to define the canonical contract for the entire API surface, ensuring consistency across all resource types and error handling.
Uses this to build a standardized framework that guarantees all services expose data using a unified envelope format.
What Changes When You Connect
- Prevents Breaking Changes: The
validate_api_designtool forces you to define versioning and resource semantics. You won't ship an endpoint that breaks a consumer's client library just because you changed a field name. - Guarantees Consistent Payloads: You stop dealing with raw objects and raw arrays. The tool demands a unified envelope structure for all responses, so client parsing is simple and predictable.
- Fixes HTTP Misuse: Instead of using
GETfor creation, the tool flags these errors immediately. It keeps your API semantics clean, making it easier for clients to use HTTP caching and standard methods. - Handles Scale: By checking for bounded pagination, the tool forces you to set max page sizes and cursor strategies. This stops memory leaks and API timeouts when a query returns too many records.
- Professional Error Handling: It requires error responses to follow RFC 7807. This means when something breaks, your clients get a structured error payload, not a useless stack trace.
- Mandates Contract-First: It shifts your workflow. You define the full contract—verbs, shapes, errors—first. Then, you write the backend logic to match it.
Real-World Use Cases
Refactoring a Legacy Service
The ops engineer has a messy, undocumented service. They run the API through validate_api_design. The tool immediately flags inconsistent response shapes and missing versioning. The engineer fixes the contract first, then writes the code, making the migration predictable.
Building a New Microservice
A team is starting a new user management service. They run validate_api_design at the outset. The tool forces them to define versioning (/v1/) and mandates a consistent response envelope for all endpoints, preventing structural debt from day one.
Implementing Complex Filtering
The team needs an endpoint to list filtered records. Before writing the query, they run validate_api_design. The tool forces them to implement cursor-based pagination and define the error contract, guaranteeing the endpoint is robust enough for scale.
Migrating from Raw JSON APIs
A client expects raw JSON data, but the team knows that's bad practice. They use validate_api_design to mandate a standard envelope and RFC 7807 error structure. The resulting API is much more reliable and easier for any client library to consume.
The Tradeoffs
GET for Modification
Using a GET /users/status endpoint to trigger an account update. This violates HTTP semantics because GET requests are designed to be read-only and idempotent.
→
Don't use GET. Instead, use a POST /v1/users/status endpoint. The tool will catch this, forcing you to respect the intended verb usage.
Inconsistent Payloads
Returning a simple user object on the /user/{id} endpoint, but returning an array of user objects on the /users list endpoint. Client code breaks trying to parse two different shapes.
→
Force a unified envelope. The tool requires all endpoints to return { data: T, meta?: {}, errors?: [] }, making client parsing consistent everywhere.
Ignoring Pagination
Writing a list endpoint that returns 10,000 records in a single payload because the dataset is 'small.' This causes massive memory spikes and API timeouts.
→
Use validate_api_design to mandate pagination. It forces you to implement limit-offset or cursor-based limits and define a maximum page size.
When It Fits, When It Doesn't
Use this if your primary concern is API stability and developer experience. If you're building a public API or an internal service consumed by multiple microservices, you need this. The tool enforces a 'contract-first' development pattern, which is critical for any system that must scale and remain predictable.
Don't use this if you are just building a single, self-contained utility script that never talks to another service. For those, simple schema validation might be enough. If your system is simple, you don't need the full rigor of validate_api_design.
When in doubt, run it. The cost of running the check is negligible compared to the cost of a production API failure.
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.
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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 server provides 1 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Building an API shouldn't involve guessing game after guessing game.
Building an API usually starts with endpoints: `/users`, `/orders`, etc. Developers write the code, and only later do they realize that the data structures and error handling are inconsistent across routes. They end up building client libraries full of custom parsers and conditional logic just to handle the messy, evolving contracts.
With API Design Prover, you define the contract first. You run the design through `validate_api_design`. The tool spits out a clean pass/fail report, forcing you to standardize everything—the data shape, the versioning, the error contract—before you write a single line of backend code.
API Design Prover MCP Server: Enforce Semantic Verbs and Contracts
You eliminate the guesswork around HTTP verbs. Instead of debating if a specific action should be `GET` or `POST`, the tool validates that your verb usage adheres to strict HTTP semantics. It also makes sure your error payloads are structured, not just raw text.
The result is an API that doesn't just work; it's predictable. It's built on a rock-solid, versioned contract that any consumer, human or agent, can reliably integrate with.
Common Questions About API Design Prover MCP
How does the API Design Prover MCP Server help with versioning? +
It validates that your design includes a clear versioning strategy (like a URL prefix /v1/). This prevents simple layout changes from becoming breaking changes for consumers.
Is the validate_api_design tool only for large APIs? +
No. It works on any API surface. It checks for five structural flaws—verb misuse, inconsistent envelopes, pagination limits, versioning, and error contracts—regardless of size.
What is the primary benefit of using validate_api_design? +
The primary benefit is shifting your workflow to 'contract-first.' You define the API structure and validate it with the tool before writing any backend logic.
Does validate_api_design handle complex data types? +
It focuses on the structure of the data (the envelope, the shape, the fields), ensuring consistency. It assumes the underlying data types are handled by your backend implementation.
How does the validate_api_design tool enforce semantic verbs? +
It validates that HTTP verbs match their intended use. The tool forces you to use GET for read-only operations and POST for resource creation, preventing semantic errors before code is written.
Can the validate_api_design tool handle inconsistent response envelopes? +
Yes, it flags structural inconsistencies in your data returns. It requires every endpoint to use a unified envelope format (like { data: T, meta: {} }), so your client code doesn't break.
What inputs does validate_api_design need regarding pagination? +
You must specify the pagination strategy and the maximum page size. The tool ensures you define limits (limit-offset or cursor-based) and prevent unbounded queries.
Does validate_api_design account for standard error contracts? +
It checks for adherence to standard error structures, like RFC 7807. This means your error responses include specific fields (type, title, status) that your agent can programmatically read.
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.
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