Assertible MCP for AI. Test, Sync, and Validate Your APIs via Chat.
Works with every AI agent you already use
…and any MCP-compatible client








How this MCP server connects to your AI agent
Assertible lets you automate API testing and monitoring directly from your AI client. You can trigger deployments, run full service test suites, sync complex specifications like OpenAPI or Swagger, validate JSON documents against specific schemas, and get status badges—all by chatting with your agent.
What AI agents can do with Assertible Automation
Create deployment
This tool initiates a new deployment for an API and automatically starts running the associated test suite.
Get service status badge
Retrieves a ready-to-use status badge URL or markdown snippet that shows the current health of an entire service.
Get test status badge
Gets a status badge URL and markdown specifically for one individual test case, so you know exactly what's passing or failing.
It creates a new deployment instance for an API service, which immediately kicks off automated testing.
You can run every single test defined for an entire API service to check its overall health and stability.
The system checks if a given piece of JSON data matches a specific, predefined schema draft, confirming structural integrity.
It pulls the latest version of your API definition—whether it's OpenAPI, Swagger, or Postman—to keep all your tests current.
Ask an AI about this
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What AI agents can do with Assertible: 7 Tools for API Quality
These tools allow you to manage the entire lifecycle of your APIs—from deployment tracking to data validation—all within a single conversation with your AI agent.
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 Assertible on VinkiusCreate Deployment
This tool initiates a new deployment for an API and automatically starts running the associated test suite.
Get Service Status Badge
Retrieves a ready-to-use status badge URL or markdown snippet that shows the current...
Get Test Status Badge
Gets a status badge URL and markdown specifically for one individual test case, so...
Run Service Tests
It runs every single available test defined for an entire API service to give you a...
Run Specific Test
This tool lets you execute only one targeted, specific test case when you need to...
Sync Specification
It pulls the latest version of your API definition from sources like OpenAPI or Swagger, keeping all your tests accurate.
Validate Json
You submit a JSON document and it checks that data against a specific JSON Schema Draft 4 to ensure it's structured correctly.
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 every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Assertible, 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
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
Built on the Model Context Protocol (MCP) for 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 7 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
The Daily Grind: Testing APIs Used to Be a Manual Chore, Solved with Vinkius AI Gateway
Today, checking an API's health is a pain. You have to switch between three places: the CI/CD dashboard for deployment status; a separate schema tool just to validate JSON inputs; and then finally run a dedicated test suite via command line. It’s tedious copy-pasting across multiple tabs and dashboards.
With this MCP, you skip all that clicking. You simply tell your agent, 'Check if the API is ready for production.' The entire process—checking status badges, running full services tests, and even syncing specs first—happens in a single conversation. You get instant confirmation, without leaving your chat.
Assertible MCP: Getting Confidence in API Quality
The manual steps that vanish are the context switching and the constant need to check which version of the specification you're using. You no longer have to manually run every single test, nor do you worry about whether your local schema matches what's live.
What changes now is that API confidence isn't a separate process; it's built into how you talk to your code. Your agent handles the heavy lifting, giving you actionable results on demand.
What your AI can actually do with this
Managing an API's quality usually means running a bunch of scripts, checking multiple dashboards, and manually updating specs. This MCP lets you ditch the console commands and just talk to your AI client. You tell it what needs testing, and it handles the rest. Need to see if a new version is stable? Your agent can trigger deployments and run all necessary tests for that service, giving you instant feedback on uptime and reliability.
If a change breaks something, you know right away. Plus, when your API specs update, you don't have to manually re-import them; the MCP handles syncing OpenAPI or Swagger files automatically. And if you just need to check if some incoming data is valid, you can validate JSON against a schema without leaving your chat window.
It’s all about making sure your APIs stay reliable and that API quality checks are part of your natural conversation flow right through Vinkius.
019ea5e1-896a-7369-b569-8d516fc649f1 Here's how it actually works
The bottom line is that you manage API quality by talking naturally to your AI client instead of running multiple commands.
First, subscribe to this MCP and enter your Assertible API Token (and optional Sync Token) so your AI client can talk to the service.
Next, tell your agent what you need. For instance, ask it to run all tests for a specific service or validate a JSON payload against a schema.
Finally, your agent executes the necessary actions and gives you immediate status updates or validation results in plain text.
Who is this actually for?
This MCP targets development teams whose daily job involves maintaining high-quality, constantly changing APIs. It's built for people who get frustrated having to switch between a CI/CD dashboard, a schema validator, and their local IDE just to verify one small change.
You use this MCP to automate deployment tracking and trigger post-deploy tests directly from your chat window instead of SSHing into a build server.
When testing an API, you run specific test suites or check status badges without leaving the development environment. You also use it to validate JSON inputs for edge cases.
You keep your project up-to-date by syncing API specifications immediately after writing code, ensuring your tests never drift from reality.
What Changes When You Connect
You immediately know the API's status without navigating multiple dashboards. Just ask your agent to get a service badge, or check one test with run_specific_test.
When you make code changes, you sync_specification to update your OpenAPI documents instantly. This means your tests always match your actual running API structure.
Debugging is faster because if something breaks after a deploy, you can trigger a new deployment using create_deployment and see the results immediately in your chat thread.
Need to ensure data coming into the system is clean? You use validate_json to check any JSON payload against a schema right where you're working. No separate validation tool needed.
The entire testing process feels natural. Instead of writing run_service_tests, you just ask your agent, 'Check the API health,' and it runs everything for you.
See it in action
Checking Post-Deployment Stability
A DevOps engineer finishes a release. Instead of waiting 20 minutes for the CI/CD pipeline to finish, they ask their agent to create_deployment and run all tests for the new version in the chat. The agent provides real-time status updates on whether the service passed its health checks.
Verifying Schema Changes
A backend developer adds a new required field to the API. Before committing, they use validate_json to test several sample payloads against the current schema draft, confirming their data structure is correct before writing any code.
Keeping Tests Current After an API Update
A QA engineer knows the upstream team updated the Swagger definition. They use sync_specification to pull the latest OpenAPI file into their testing environment, ensuring that manually written test scripts aren't running against outdated data models.
Quickly Checking Service Health
A manager needs a quick health check before a call. Instead of logging in to the monitoring portal, they ask their agent for get_service_status_badge and include the status directly in the meeting summary.
The honest tradeoffs
Treating APIs like databases
Trying to use your AI client just to look up a user ID or fetch raw data. This MCP is for checking quality, not retrieving content.
If you need to read or write actual records, that's a database tool job. Use this MCP only when you are confirming the API service works correctly or validating its structure.
Assuming all tests run automatically
Thinking that just because code compiled successfully means the endpoints work. Compilation doesn't guarantee runtime health.
Always use run_service_tests after a build to confirm full system uptime and reliability, or narrow it down with run_specific_test if you know where the failure occurred.
Manually updating specifications
A developer manually downloading and re-uploading the latest Swagger file every time an API endpoint changes.
Use sync_specification. It automatically pulls the current OpenAPI or Swagger definition, keeping your test environment synchronized with production.
When It Fits, When It Doesn't
Use this MCP if your primary pain point is verifying the quality and contract of an API—meaning you need to know if it's stable, if its data structure is correct, or if a new version actually works. This tool excels at automating structured testing cycles. Don't use it if you simply need to perform CRUD operations (Create, Read, Update, Delete) on stored records; for that, you need a database connector. Also, if your only goal is sending simple notifications or reading user profiles, this MCP won't help. However, if the core of your work involves deploying code and ensuring those deployed endpoints are stable, then this collection of tools—like create_deployment combined with run_service_tests—is exactly what you need.
Questions you might have
How do I use Assertible MCP to check if my service is up? +
You can get an immediate status update by using get_service_status_badge. This quickly provides a markdown badge that shows whether the entire API service is currently passing or failing its health checks.
Can Assertible MCP validate JSON schemas? +
Yes, you use the validate_json tool for this. You provide the document and the schema, and it tells you if the payload conforms to the rules set in the Draft 4 standard.
What is the difference between run_service_tests and run_specific_test? +
run_service_tests runs every single test available for that service, giving you a full health picture. run_specific_test lets you pinpoint and execute only one single test case if you suspect an issue with just that function.
Does Assertible MCP help me update my API specs? +
Yes, use sync_specification. This tool pulls the latest OpenAPI, Swagger, or Postman definitions automatically, making sure your test environment is always current after an upstream change.
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