Assertible MCP. Run full API test suites and manage deployments from chat.
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Assertible gives you full control over your API quality from chat. Trigger deployments, run complete service test suites, sync OpenAPI specs, or validate JSON documents using your AI agent.
It’s built for DevOps and QA engineers who need to manage the whole CI/CD cycle without leaving their terminal.
What your AI agents can do
Create deployment
Initiates a new deployment run for an entire service and triggers all associated tests.
Get service status badge
Generates the status badge URL and markdown needed to show the current health of an entire API service.
Get test status badge
Generates a status badge URL and markdown for one specific test case, useful when diagnosing failures.
Trigger new deployments or run full test cycles across target environments using the create_deployment tool.
Run comprehensive tests for an entire service, or narrow down failure points by running a specific test ID, ensuring immediate reliability checks with run_service_tests and run_specific_test.
Keep your API definitions up-to-date by syncing specifications (Swagger, Postman, OpenAPI) using the sync_specification tool.
Check if any given JSON document matches a required schema standard instantly with the validate_json function.
Retrieve embeddable status badges and markdown for services or individual tests, giving an at-a-glance view of API health via get_service_status_badge and get_test_status_badge.
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Assertible: 7 Tools for API Quality Gatekeeping
Manage your full CI/CD pipeline by triggering deployments, running targeted tests, syncing specifications, and validating data structures using these seven tools.
019ea5e1create deployment
Initiates a new deployment run for an entire service and triggers all associated tests.
019ea5e1get service status badge
Generates the status badge URL and markdown needed to show the current health of an entire API service.
019ea5e1get test status badge
Generates a status badge URL and markdown for one specific test case, useful when diagnosing failures.
019ea5e1run service tests
Executes every available test defined for an entire service to check its overall health.
019ea5e1run specific test
Runs only a single, targeted API test by specifying its unique ID, perfect for focused debugging.
019ea5e1sync specification
Updates the service's documentation by syncing an OpenAPI, Swagger, or Postman specification file.
019ea5e1validate json
Checks if a provided JSON document adheres to a predefined JSON Schema Draft 4 structure.
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 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ 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
What you can do with this MCP connector
Assertible gives you absolute control over your API quality right from your chat client. You can trigger deployments, run full service test suites, sync OpenAPI specs, or validate JSON documents using just your AI agent. It’s built for DevOps and QA engineers who need to manage the whole CI/CD cycle without ever leaving their terminal.
Automating Your Whole Damn CI/CD Pipeline
When it's time to push code, you don't want guesswork; you want certainty. You can kick off an entire deployment run for a service using the create_deployment tool. This single command triggers every associated test suite defined for that target environment, making sure everything works before anyone else sees it.
For testing services across different environments, this function lets you manage the full rollout process and verify stability in one go.
Diagnosing API Failures Down to the Byte
When something breaks—and things break—you need to know exactly where. You can run a comprehensive set of tests for an entire service using run_service_tests, giving you a quick picture of overall health. If that broad test fails, don't sweat it; you can pinpoint the exact problem by running only a single, targeted API test.
Just provide the unique ID to use the run_specific_test function. This hyper-focused approach saves hours when debugging because you skip over all the passing tests and go straight for the failure point.
Keeping Your Specs Current and Clean
Documentation is worthless if it's lying. You gotta keep your API definitions accurate, so you can use sync_specification to update the service documentation. This tool handles syncing specifications whether they come from OpenAPI, Swagger, or Postman files. It keeps your defined structure—the source of truth for what your API is—perfectly matched with your live code.
Validating JSON Payloads Instantly
Before you even hit the service, you need to know if your data payload is structured correctly. You can use validate_json to check any given JSON document against a predefined JSON Schema Draft 4 structure. This function instantly tells you whether your provided JSON adheres to the required format or if you got mismatched brackets and bad types.
Tracking Service Status at a Glance
You don't wanna be digging through logs just to see if something is up. You need an immediate status check. Use get_service_status_badge to generate the necessary badge URL and markdown needed to show the current health of your entire API service in any communication channel. If you only care about one specific test, not the whole thing, get_test_status_badge gives you a dedicated badge for that single test case.
These tools give you an at-a-glance view—no guesswork required.
How Assertible MCP Works
- 1 Subscribe to the server on Vinkius.
- 2 Enter your Assertible API Token (and optionally your Sync Token) into your client settings.
- 3 Start asking your AI agent questions like, 'Run all tests for service X' or 'Validate this JSON against schema Y'.
The bottom line is you manage your entire API quality and monitoring process from a single chat window.
Who Is Assertible MCP For?
This tool is for the Ops Engineer who hates context switching between Jira, Jenkins, and Swagger UI. It's for the QA engineer tired of clicking through dashboards at 2 AM to check if a feature broke. If your job involves making sure an API actually works after deployment, you need this.
Automates deployment tracking and runs post-deploy test triggers directly from the chat interface.
Runs specific, targeted test suites or full service health checks without leaving their primary development environment.
Validates JSON schemas and syncs API specifications immediately after making code changes to prevent integration debt.
What Changes When You Connect
- Stop checking dashboards. Use
get_service_status_badgeto instantly get an embeddable health status for any service, giving you a quick overview without running multiple commands. - Manage the whole deployment cycle with
create_deployment. You can kick off a new version rollout and have all subsequent tests run automatically—all from one prompt. - Drill down fast. Instead of relying only on full suite runs, use
run_specific_testto check just one failing endpoint by ID. This saves time when debugging complex failures. - Keep documentation honest. If you change the API contract, use
sync_specification. This ensures your specs match reality before anyone tries to hit a broken endpoint. - Validate data payloads immediately. Use
validate_jsonto check incoming or outgoing JSON against a schema. It's an essential guardrail for backend code.
Real-World Use Cases
New Release Validation
A DevOps engineer just pushed v3.1.0. Instead of manually logging into the CI system, they prompt their agent: 'Run a deployment for service X at version v3.1.0.' The agent uses create_deployment and monitors the results, giving instant feedback on whether the full test suite passed.
Schema Drift Check
A backend developer updated their user profile endpoint to accept a new field. Before merging, they ask the agent to run sync_specification and then use validate_json with the schema to confirm the API contract is up-to-date.
Targeted Failure Debugging
QA runs a full suite of tests, but one endpoint fails. Instead of rerunning everything, they grab the specific test ID and ask the agent to run run_specific_test using that ID. They isolate the failure point in seconds.
Quick Health Check
A support engineer needs to know if a client-facing API is healthy right now. They prompt the agent for 'the service status badge.' The agent uses get_service_status_badge and returns the markdown code, allowing them to paste it directly into an incident report.
The Tradeoffs
Manual Payload Testing
Copy-pasting a JSON payload from one tool/terminal window to another for manual validation. This is slow and prone to copy errors.
→
Don't copy it. Use validate_json. Pass the raw JSON content directly to your agent, along with the schema, and let the tool confirm validity instantly.
Running Tests in Isolation
Only running run_service_tests but forgetting that a recent API change requires updating the documentation. The tests pass, but the spec is wrong.
→
Always run sync_specification before or after major test cycles. This guarantees your docs and your code are talking to each other.
Ignoring Deployment Steps
Assuming that just running a deployment trigger is enough. You might forget to check the final status badge or validation results.
→
After using create_deployment, always follow up by checking the service health with get_service_status_badge. This confirms the pipeline actually finished successfully.
When It Fits, When It Doesn't
Use this server if your core pain point is managing API quality and deployment reliability across multiple tools, and you want that management to happen conversationally. You need automated gatekeeping—this means you're dealing with services that must maintain uptime and contract integrity.
Don't use this if all you need is a simple JSON linter or basic documentation hosting. If your requirement is just 'check if this payload looks okay,' validate_json handles it, but the server provides much more depth by tying validation into deployment workflows.
Use this when you need to sequence actions: e.g., 'Sync specs -> run tests -> check status.' The tools allow that orchestration directly through your AI client.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Assertible. 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 7 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Checking API health shouldn't mean opening five different dashboards.
Today, checking if a new deployment is safe means jumping between the CI dashboard to see test status, then switching to Swagger UI to check endpoints, and finally logging into the monitoring tool just for a general 'up/down' badge. It's clicking through half a dozen tabs, making it slow and tedious.
With Assertible, you simply ask your agent to confirm the service health. The agent runs `run_service_tests` in the background and gives you the result—a clean, embeddable status badge right in the chat. You get visibility without the context switch.
Assertible MCP Server: Run full API test suites from chat.
The painful manual process involves running tests locally, then pushing them to a staging environment, and waiting for the CI/CD pipeline to finish. You're constantly monitoring logs in one window while verifying results in another.
Now, you just tell your agent: 'Create deployment for service X.' The agent uses `create_deployment`, manages the entire run cycle, and reports back on success or failure status immediately. It handles the whole sequence.
Common Questions About Assertible MCP
How do I check if a JSON document is valid using validate_json? +
You provide validate_json with three things: the raw JSON content, the schema draft number (Draft 4), and the specific JSON Schema rules. The tool returns true/false and any errors found against your defined contract.
What is the difference between run_service_tests and run_specific_test? +
run_service_tests runs every single test available for that service, giving a complete health picture. run_specific_test lets you target one known failing endpoint by its ID, saving time when you know where the problem is.
Do I need to use sync_specification before creating a deployment? +
It's best practice. Running sync_specification first ensures that your API documentation (OpenAPI/Swagger) matches what's actually deployed, so the test results are based on accurate contract information.
Can I see the current status of a service using get_service_status_badge? +
Yes. You pass the service ID to get_service_status_badge, and it returns the markdown code you need, letting you embed the real-time health badge anywhere in your chat or documentation.
What authentication details do I need when calling `sync_specification`? +
You must provide an Assertible API Token and, if syncing a specification, you'll also need the ASSERTIBLE_SYNC_TOKEN. These tokens grant your AI client permission to update service specifications.
How do I know if a deployment triggered by `create_deployment` failed? +
The tool initiates tests and reports status, but you must use get_service_status_badge afterward. This lets you check the final pass/fail status for the entire service after the deployment attempt.
Does `sync_specification` support different API standard formats? +
Yes, it handles multiple specification types. You can sync specifications written in OpenAPI, Swagger, or Postman format into your environment.
If I only care about one specific test result, should I use `get_test_status_badge`? +
That's the right tool. While service status is useful, get_test_status_badge lets you isolate and retrieve the status badge for a single, specific test by ID.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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