Apidog MCP for AI Agents. Access API Specs and Schemas via Chat.
Apidog MCP connects your AI agent directly to your API specification library. You can list projects, fetch deep schemas for any endpoint, and export the full OpenAPI 3.0 JSON without leaving your chat environment. Get instant access to every data model and HTTP route defined in Apidog.
Give Claude and any AI agent real-world access
Lists every active project in your connected Apidog organization so you know what APIs exist.
Retrieves all specific HTTP routes and endpoints defined inside one chosen Apidog project.
Fetches the complete technical blueprint, including request/response body schemas, for any single API endpoint.
Lists all reusable data structures (like DTOs or entities) defined across your entire Apidog workspace.
Extracts the full, standardized OpenAPI 3.0 JSON file for a project, giving you maximum context.
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What AI agents can do with Apidog MCP - 5 Tools
Use these tools to programmatically access and extract every API project, endpoint schema, data model, and the full OpenAPI specification from your Apidog account.
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 Apidog MCPList Projects
Retrieves a list of every API project that exists in your Apidog organization.
List Endpoints
Gives you a comprehensive list of all HTTP routes defined within one specific Apidog...
Get Endpoint
Pulls the complete technical schema for any single API endpoint, showing its methods...
List Schemas
Lists all defined data models or reusable schemas (DTOs, entities) used across your...
Export Openapi
Exports the full OpenAPI 3.0 specification file for a selected project in JSON...
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.
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 each call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Apidog, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,200+ others, all in one place
- Add new capabilities to your AI anytime you want
- Connections are secured and governed automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog weekly
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API documentation used to feel like a massive scavenger hunt. Solved with Vinkius AI Gateway
Today, getting a clear picture of your API contracts means jumping between five different tabs. You open the project dashboard to see what exists, click into an endpoint to check parameters, and then copy-paste the schema definition—a messy process that usually ends with you forgetting which version was correct.
With this MCP, you simply ask your agent for it. It handles all the clicks behind the scenes, giving you a clean, single output of the full OpenAPI JSON or a precise data model. You get actionable context instantly.
Apidog MCP: Get structured API specs with one prompt.
The tedious steps that vanish include manually navigating through projects using list_projects, then opening dozens of individual endpoints to check their schemas via get_endpoint. You also stop worrying about losing track of shared data formats by using list_schemas.
Now, you treat your entire API contract like a conversation. The technical details are available on demand, right where you're writing code or building tests.
What your AI can actually do with this
Need to understand an API contract without clicking through a dozen tabs? Connect this MCP and let your AI agent handle it. You can ask your agent to list all existing projects, instantly seeing the full scope of your organization’s APIs. Need details on one specific route? Your agent pulls the complete schema for that endpoint—headers, path parameters, and body structures included.
Better yet, if you need context for unit testing or code generation, your agent can pull every reusable data model (DTOs, entities) defined in Apidog. When you're ready to scaffold a whole service, simply ask it to export the complete OpenAPI 3.0 JSON specification. This capability makes advanced API documentation immediately available right within your chat interface, giving your AI client maximum context for testing or building new codebases.
Because Vinkius hosts this MCP, you connect once from any compatible agent and get access to all of Apidog's powerful tools.
019d754f-2c27-72df-8129-68a631fc8598 Here's how it actually works
The bottom line is you talk to your API documentation using plain English instead of navigating through complex web dashboards.
Subscribe to this MCP and provide your Apidog Personal API Access Token.
Your AI client authenticates and gains access to all of your API contracts stored in the Apidog workspace.
You prompt your agent with a natural language request, like 'Show me the schema for /users,' or 'Export the OpenAPI JSON.' The agent executes the necessary tool call and returns the structured data.
Who is this actually for?
This MCP is for developers who spend too much time manually switching between their IDE, Postman, and internal documentation pages just to confirm an API contract. It saves the Backend Developer from context-switching and helps QA teams build reliable test cases faster.
Uses the agent to quickly review endpoint details or export a full OpenAPI specification so the AI can safely scaffold controllers or unit tests.
Asks the agent to inspect an Apidog schema and generate corresponding TypeScript interfaces, eliminating manual type definition.
Automates the fetching of expected response payloads for multiple endpoints to construct robust integration tests without accessing the UI.
What Changes When You Connect
Stop copying schemas manually. Using the agent to inspect endpoint schemas means you get clean, structured data for immediate use in your code.
Never lose context again. The ability to export the full OpenAPI 3.0 JSON specification lets your AI client have maximum information when generating unit tests or scaffolding entire services.
Save time listing APIs. Instead of clicking into projects one by one, you can ask the agent to list all active projects in your organization instantly.
Keep code types consistent. You can use the tool to query and get a list of every data model defined, ensuring your front-end interfaces match the backend contract.
Streamline testing setup. QA teams gain an automatic way to fetch expected response payloads using the agent, making integration test construction much faster.
See it in action
Building a new microservice
A backend developer needs to scaffold five controllers for a new 'Billing' service. Instead of jumping through Apidog to find every endpoint, they ask the agent to use list_projects and then export_openapi for the Billing API. The resulting JSON provides everything needed for the AI client to generate all necessary boilerplate code in one go.
Updating a legacy front-end
A frontend engineer needs to update their TypeScript models because an internal API changed its response structure. They use get_endpoint on the old route, letting the agent pull the precise schema definition and generate the correct interfaces for their client code.
Writing complex integration tests
The QA team has a module that hits multiple endpoints (GET /users, POST /orders). They use list_schemas to see every possible data structure. Then, they instruct the agent to fetch expected response payloads for each route, building robust test cases without manual inspection.
Onboarding a new developer
A junior developer needs an overview of all available APIs in a large system. They ask the agent to use list_projects first, then follow up by listing endpoints for a specific project, getting them oriented quickly without needing institutional knowledge.
The honest tradeoffs
What to watch out for, and the recommended way to handle each one.
Manual schema comparison
You open Apidog to check the response body of /items, copy the JSON structure into a separate doc, and then paste it into your IDE. You repeat this for every endpoint.
Instead, ask your agent to use get_endpoint on that route. It instantly pulls the full schema and gives you clean, structured data right in the chat window.
Ignoring API contracts
Your team assumes a new endpoint will return user_id when it actually returns userId, causing runtime bugs that only appear in staging.
Always use list_schemas first. This guarantees your agent sees the actual, defined data models and confirms the exact field names before you write any code.
Overlooking project scope
You only look at a single endpoint's documentation page, missing related resources or other endpoints in the same service.
Start by listing all API projects using list_projects. This shows you the entire landscape of APIs and helps you gather context before diving into any specific route.
When It Fits, When It Doesn't
Use this MCP if your primary bottleneck is accessing, comparing, or exporting structured information from API specifications. If you need to know what an endpoint expects or returns—its headers, its parameters, or its data types—this tool gives you immediate access via chat commands. Don't use it if you need to modify the underlying Apidog service or manage user permissions; this MCP is purely for reading and extracting documentation. If your goal is simply to browse a GUI-based visual flow chart of the API, stick with the native Apidog client. But if you need to integrate that specification data into an automated workflow, writing unit tests, or generating code from multiple sources, this MCP is essential.
Questions you might have
How does Apidog MCP help me with unit testing? +
It helps by letting your agent export_openapi. You get the complete OpenAPI 3.0 JSON specification, which gives your AI client all the necessary context (endpoints and schemas) to write comprehensive tests.
Can I see every project in my organization using Apidog MCP? +
Yes, you use list_projects. This tool immediately shows you a roster of all active API projects within your connected Apidog workspace.
What if I need to check the parameters for one endpoint in Apidog MCP? +
You run get_endpoint. The agent pulls the full schema, detailing everything from HTTP methods and path params to required headers and body structure.
Is the data model information limited when using list_schemas? +
No. list_schemas queries all reusable schemas—the DTOs and entities—that your API uses across multiple endpoints, keeping your whole system's type definitions in one place.
Does Apidog MCP work with my existing code base? +
Yes. By providing the full OpenAPI JSON via export_openapi, you give your AI client all the necessary documentation to scaffold controllers or generate service layers that match your existing codebase.