AI app for it and development · no coding needed
Source-linked API specification and agent-readiness workbench
Reduce specification drift and manual tool switching while keeping API contracts under named-owner review.
Made for: API platform teams, developer-experience engineers and integration leads maintaining OpenAPI specifications
What it does for you
The problem
API specifications drift from code, lint and test steps live in separate tools, and agent-ready contracts are assembled by hand.
What it gives you
Reviewed, source-linked API contracts and agent-ready tool definitions
What you give it
Supplied specificationscode repositoriesPostman collectionsSDKs
Build your own version of Cursor for your API, create-api.dev by Kong and more
One app with what these 4 AI tools do, yours to keep and change: Cursor for your API, create-api.dev by Kong, Elva, Swytchcode.
Everything these tools do, in one app
- OpenAPI spec generation Creates OpenAPI specifications from user descriptions or imports existing specs.Found in Cursor for your API, create-api.dev by Kong
- AI-assisted spec editing Suggests edits to API specifications using AI, with a diff shown before acceptance.Found in Cursor for your API
- Integrated linting Checks API specifications for errors and style issues within the same interface.Found in Cursor for your API
- Documentation preview Shows a preview of the API documentation generated from the specification.Found in Cursor for your API
- In-tool API testing Lets users run API calls and validate endpoints with real inputs without leaving the tool.Found in Cursor for your API, Swytchcode
- API design and DX insights Provides feedback on API design quality, developer experience, security, and AI-readiness.Found in Cursor for your API
- Browser-local processing Runs all processing in the browser with no server-side storage of specs or keys by default.Found in Cursor for your API
- Bring your own model key Allows users to supply their own API key and choose the AI model.Found in Cursor for your API
- MCP export Exports APIs in a format that makes them consumable by AI agents via Model Context Protocol.Found in Cursor for your API
- No login required Enables immediate use without account creation or setup.Found in create-api.dev by Kong
- Spec sharing Provides built-in sharing capabilities for collaboration and feedback on API designs.Found in create-api.dev by Kong
- AI Gateway integration Connects with Kong's AI Gateway to enhance spec quality and safety.Found in create-api.dev by Kong
- Open source renderer Uses an open source spec renderer for transparent and customizable output.Found in create-api.dev by Kong
- API discovery from code Scans code repositories to map out APIs, usage patterns, and AI readiness without needing a spec.Found in Elva
- Audience-specific contracts Controls which endpoints and fields are exposed to different customers, partners, or agents.Found in Elva
- Hosted MCP servers with auth Runs MCP servers with authentication and enforces permissions at the tool and resource level.Found in Elva
- Agent observability Tracks which agents and users call which tools, including latency, error rates, and agent feedback.Found in Elva
- Change review workflow Flags API drift when code changes and supports automatic sync or manual approval with notifications.Found in Elva
- CLI access Provides command-line interface access for managing APIs.Found in Elva
- Spec and SDK ingestion Accepts OpenAPI, Postman, and SDKs and maps them into an internal format for AI consumption.Found in Swytchcode
- Interactive docs and playgrounds Automatically generates interactive documentation and playgrounds for testing endpoints.Found in Swytchcode
- Code and workflow generation Produces example code and multi-step workflows in multiple languages.Found in Swytchcode
- MCP-based code queries Supports Model Context Protocol to query and generate code through editor integrations.Found in Swytchcode
How it works, step by step
- Generate OpenAPI specifications from descriptions or imports
- Suggest AI-assisted spec edits with a diff before acceptance
- Lint specifications for errors and style issues in the same interface
- Preview generated API documentation
- Run API calls and validate endpoints with real inputs in-tool
- Report API design, developer-experience, security and AI-readiness insights
- Process specifications and keys in the browser by default
- Accept a user-supplied model key and model choice
- Export APIs as MCP tool definitions for AI agents
- Allow immediate use without account creation
- Share specifications for collaboration and feedback
- Connect to an AI gateway for spec quality and safety checks
- Render output through an open source spec renderer
- Scan code repositories to map APIs, usage patterns and AI readiness
- Control which endpoints and fields are exposed to each audience
- Run hosted MCP servers with authentication and tool-level permissions
- Track agent and user tool calls, latency, errors and feedback
- Flag API drift on code change and support sync or manual approval
- Provide CLI access for API management
- Ingest OpenAPI, Postman and SDKs into an internal format
- Generate interactive documentation and playgrounds
- Produce example code and multi-step workflows in multiple languages
- Query and generate code through MCP editor integrations
- Compare the reviewed result with the recorded baseline and value assumptions
- Capture corrections and named-owner approval before consequential use
- Export a versioned reviewed API contract with source references and unresolved questions
Build it yourself with your AI system
Build this app yourself, no coding needed
Start with a quick version you can try in a few minutes. Like it? Then build the full app by copying and pasting our step-by-step instructions: everything is prepared for you.
Sign in to see how to build it yourself
Build a quick version to try, or get the full app pack for Source-linked API specification and agent-readiness workbench with the step-by-step building instructions. You don't need any technical skills: you copy, paste and answer a few questions. Both are included in the membership.
4 Have it built for you days to a few weeks
Rather not do it yourself, or want it fully tailored to your data, your way of working and your brand? Nexibeo builds Source-linked API specification and agent-readiness workbench with you.
What's in the app pack
Included in the Complete AI Training membership.
- The building instructions your AI follows, step by step
- The questions your AI will ask you about your business before it starts
- A clickable demo you can open in your browser, to see how it should work
- A detailed blueprint of the screens, the information it keeps and the checks it runs
Become a member to get the app packAlready a member? Sign in
The files, for the technically curious
- START-HERE.mdHow to build it with your own AI (read first)3 KB
- README.mdOverview and links5 KB
- questions.mdQuestions to answer before you build2 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare27 KB
- prompt-vps.mdThe same build on your own server (Docker)27 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria14 KB
- demo/index.htmlThe working demo on sample data197 KB
Questions
Do I need to know how to code?
No. You copy and paste the prompts on this page into ChatGPT or Claude, and the AI does the building. When it asks you something, you answer in your own words.
What does it cost?
The quick version, the app pack and the step-by-step instructions are for members: you pay the membership price, not a price per app (see the plans). Building the full app uses your own ChatGPT or Claude subscription. Putting it online is often cheap or no cost at the start, and your AI tells you before anything costs money.
How long does it take?
The quick version: about two minutes. The real app: an afternoon for a first version you can use, longer if you want every feature.
Can I change it to fit my business?
Yes. Tell your AI what to change in plain words, like “add a column for the price” or “use our logo and colours”. Or have Nexibeo build and customise it for you.
More detailsHow the AI works, safeguards and what to build first
Reduce specification drift and manual tool switching while keeping API contracts under named-owner review. For API platform teams, developer-experience engineers and integration leads maintaining OpenAPI specifications, convert supplied specifications, code repositories, Postman collections and SDKs into reviewed, source-linked API contracts and agent-ready tool definitions. The benefit is a testable hypothesis, measured through accepted specification revisions per engineering hour and drift incidents after publication; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect supplied specifications, code repositories, Postman collections and SDKs, then follow this sequence: 1. Generate OpenAPI specifications from descriptions or imports. 2. Suggest AI-assisted spec edits with a diff before acceptance. 3. Lint specifications for errors and style issues in the same interface. 4. Run API calls and validate endpoints with real inputs in-tool. 5. Report API design, developer-experience, security and AI-readiness insights. Resolve uncertain cases with qualified reviewers, approve reviewed, source-linked API contracts and agent-ready tool definitions, and measure accepted specification revisions per engineering hour and drift incidents after publication against a documented baseline.
How the AI works
Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the stated task modules. Use deterministic code for schema validation, lint rules, arithmetic and reproducible tests. Review source-linked explanations and uncertainty before accepting results. Browser-local processing by default; hosted MCP servers and gateway checks require explicit configuration. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve source attribution, schema accuracy, security boundaries and usage permissions. API owners approve substantive contract changes and publication scope. One approved specification format and one repository source; final contract and security decisions remain with the API owner. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.
What to build first
Pilot scope: One approved specification format and one repository source; final contract and security decisions remain with the API owner. Implement one approved input format, a bounded representative case set and the first three task modules: generate OpenAPI specifications from descriptions or imports; suggest AI-assisted spec edits with a diff before acceptance; lint specifications for errors and style issues in the same interface. Support the remaining modules with operator review. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.
What it can connect to
Customer-owned specifications, code repositories, Postman collections and SDKs. Cloud source control, CI pipelines, API gateways and documentation destinations. Start with file exchange and validate destination specifications before promising direct publishing. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.
The screens in detail
Primary screens: Specification workspace, Source-linked review, Agent and audience console. Use a project list for APIs, a large central editor with diff view, and a right-hand panel for lint findings, test results, design insights and comments. Let users compare spec versions side by side. Display draft, changes requested and approved states. Provide a share link with comments anchored to the relevant endpoint or schema. Make the task-specific outcome reviewed, source-linked API contracts and agent-ready tool definitions visible beside its evidence, review state and value baseline.
