Levo.ai MCP. Audit API Flows and Data Exposure Instantly
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
Levo.ai (API Security & Observability) connects your AI agent to deep API traffic analysis. It audits endpoints for PII and PHI, checks for OWASP vulnerabilities like BOLA, and exports live OpenAPI specifications from actual usage patterns.
What your AI agents can do
Export openapi spec
Exports a live, auto-generated OpenAPI specification file based on observed API traffic.
Get endpoint details
Retrieves the deep schema structure for one specific discovered API endpoint.
Get observation
Gets detailed information about a single, identified runtime anomaly in API traffic.
The agent lists and categorizes all API endpoints that handle sensitive data flows, including PII and PHI.
It maps every live API endpoint—REST, GraphQL, gRPC, or SOAP—including undocumented shadow services.
The agent checks active API traffic against OWASP standards to find security flaws like BOLA instances and broken authentication.
It creates accurate OpenAPI specification files based on the actual request and response data observed in live traffic.
You retrieve detailed reports on unexpected runtime API behavior, like schema drift or unusual access patterns.
Ask AI about this MCP
Supported MCP Clients
Gemini Waiting for input…
Levo.ai (API Security & Observability): 10 Tools
These tools allow your agent to perform deep API analysis: discovering endpoints, checking for vulnerabilities, auditing data flow, and generating accurate specs.
019d75c6export openapi spec
Exports a live, auto-generated OpenAPI specification file based on observed API traffic.
019d75c6get endpoint details
Retrieves the deep schema structure for one specific discovered API endpoint.
019d75c6get observation
Gets detailed information about a single, identified runtime anomaly in API traffic.
019d75c6get vulnerability
Retrieves full diagnostic evidence for a specific API vulnerability to understand the root cause.
019d75c6list applications
Lists every major API application (service) that Levo.ai is currently tracking.
019d75c6list catalog endpoints
Identifies and lists all discovered API endpoints—including undocumented shadow services—across REST, GraphQL, gRPC, and SOAP.
019d75c6list environments
Lists the various deployment environments being monitored by Levo's active sensors (e.g., staging, production).
019d75c6list observations
Pulls a list of all detected runtime API behavior observations from the live sensors.
019d75c6list sensitive data
Lists which API endpoints are exposing sensitive or regulated data flows (PII, PHI, etc.).
019d75c6list vulnerabilities
Provides a list of all active security vulnerabilities discovered across every tracked application.
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 Levo.ai (API Security & Observability), 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
Levo.ai API Security & Observability connects your agent to deep API traffic analysis. You audit endpoints for PII and PHI; you check for OWASP vulnerabilities like BOLA; and you export live OpenAPI specifications straight from actual usage patterns.
Your AI client interacts with live API data, not static code. It lets you see what's running right now—even the stuff nobody documented.
Mapping Out Your Infrastructure:
You start by seeing every major service Levo.ai is tracking via list_applications. You can also check which deployment environments are being monitored with list_environments, like staging or production.
To map your entire attack surface, you run list_catalog_endpoints. This tool finds every API endpoint—that includes REST, GraphQL, gRPC, and SOAP types. It doesn't miss the undocumented shadow services either.
Next, you identify where sensitive information leaks. You use list_sensitive_data to pull a list of endpoints that handle protected data flows, including PII and PHI. For deeper context on any single endpoint, run get_endpoint_details to retrieve its complete schema structure.
Scanning for Flaws:
You don't wait for an audit; you watch the traffic live. list_vulnerabilities gives you a full list of security flaws detected across every tracked application. When you find one, get_vulnerability provides all the diagnostic evidence so you know exactly why it's broken and how to fix it.
Observing Behavior:
You track what actually happens in traffic with observation tools. Run list_observations to pull a list of every detected runtime anomaly from the live sensors. If you spot a weird issue, get_observation gives you detailed info on that specific event, like if the data schema suddenly drifted or access patterns got unusual.
Generating Docs and Specs:
When development is done, you need accurate documentation. You run export_openapi_spec, which immediately generates an OpenAPI specification file based on the actual request and response data it's seeing in live traffic. This means your docs always match what the API does. The combination of endpoint discovery, vulnerability checks, and real-time observation gives you total visibility over your API security posture.
How Levo.ai MCP Works
- 1 Subscribe to this server and provide your Levo.ai API Token and Organization ID.
- 2 Connect the MCP Server to your preferred AI client (Claude, Cursor, etc.).
- 3 Ask your agent a specific question—for example, 'List all endpoints exposing PII'—to trigger the security scan.
The bottom line is you talk to your API security posture like it’s just another service endpoint.
Who Is Levo.ai MCP For?
Security Engineers who are tired of manually sifting through massive log files. Backend Developers who need proof that a new feature's API schema is secure before merging code. Compliance Officers needing an automated, auditable report on regulated data flows across all environments.
Uses list_vulnerabilities and get_vulnerability to hunt for specific API threats without writing complex regex filters.
Runs checks using export_openapi_spec or get_endpoint_details to validate the schema of new endpoints against security rules.
Automates reports by calling list_sensitive_data across multiple deployment boundaries (list_environments) for audit trails.
What Changes When You Connect
- Stop guessing about your APIs. Use
list_catalog_endpointsto map all endpoints—including those undocumented 'shadow' services that are silently leaking data. - Move past static code reviews. By running
get_vulnerabilityagainst live traffic, you catch real-world flaws like BOLA instances, not just theoretical ones. - Compliance reporting gets faster. Call
list_sensitive_dataand specify your regulated data type (PII/PHI) to get an immediate, auditable list of exposure points. - Documentation syncs with reality. Instead of manually updating specs,
export_openapi_specgenerates a definition based on what the API is doing right now. - Investigation is deep. If something breaks, running
get_observationgives you specific diagnostic evidence to understand exactly why and how to fix it.
Real-World Use Cases
Pre-Launch Security Audit
A developer wants to know if their new 'Checkout' microservice is safe. They use list_applications to confirm the service exists, then run list_vulnerabilities. The agent reports two high-impact flaws: BOLA and broken auth. The dev fixes these issues before merging anything.
Compliance Report Generation
A compliance officer needs to prove that PHI is not accessible outside of the 'Medical Records' environment. They run list_sensitive_data and filter by PHI, checking all environments via list_environments. The system confirms only authorized endpoints expose this data.
Incident Response (Mystery Leak)
An alarm triggers about an unknown data leak. A security engineer runs list_observations to find the anomaly. They then use get_observation to drill down, pinpointing which endpoint and which specific payload caused the unexpected schema drift.
Updating API Documentation
The team adds a new internal reporting feature. Instead of manually updating the OpenAPI file, they run list_catalog_endpoints to find the new routes, then use export_openapi_spec to generate a 100% accurate spec immediately.
The Tradeoffs
Only checking source code
Assuming that because the API endpoint is written correctly in the codebase, it cannot be vulnerable. This misses issues caused by runtime configuration or improper access controls.
→
You must use list_vulnerabilities and get_vulnerability. These tools check the live traffic against OWASP standards—not just the code.
Ignoring undocumented APIs
Manually listing endpoints, which always results in missing 'shadow' or zombie APIs that are still active and exposing sensitive data.
→
Start by calling list_catalog_endpoints. This tool finds every endpoint—including the undocumented ones—so nothing slips through your audit.
Using general log search
Searching massive, raw log files for 'PII' without knowing if that data is regulated or where it came from. This creates noise and misses context.
→
Use list_sensitive_data. It doesn't just find the word; it flags endpoints specifically categorized as exposing PII or PHI.
When It Fits, When It Doesn't
Use this server if your primary pain point is 'visibility.' If you need to know everything that exists, how it behaves under load, and if the data passing through it meets compliance standards—then this is what you use. It's designed for deep, proactive security auditing.
Don't use this if your only goal is basic uptime monitoring (use a simple health check tool) or if you just need to retrieve one single piece of data without checking its context. If all you need is a list of applications, start with list_applications, but remember that for true security assurance, you must follow up by running checks like list_vulnerabilities and list_sensitive_data. This tool forces you into a holistic view: discovery -> inspection -> action.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Levo.ai. 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.
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
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 10 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Finding every API endpoint shouldn't require sifting through three different log tabs.
Today, if you want to audit an API service, you usually have to check the source code repository for defined endpoints. Then, separately, you must dig into runtime logs—sometimes requiring multiple filters for 'error,' 'warning,' or specific headers—just to find out what services are actually active and where they might be leaking data.
With this MCP server, you ask your agent once: 'Show me all API endpoints.' The agent runs `list_catalog_endpoints` and gives you a single, unified list that includes every service, even the undocumented ones. It’s discovery without the dashboard headache.
The export_openapi_spec tool provides documentation that actually matches reality.
Traditionally, API developers create OpenAPI specifications manually or generate them from simple request examples. This often means the document is outdated before it even hits production—it misses edge cases, schema changes, and new routes entirely.
Now, you simply call `export_openapi_spec`. It analyzes the live traffic and generates a specification that reflects exactly what the API is doing right now. The documentation always stays synced with reality.
Common Questions About Levo.ai MCP
How does list_sensitive_data work for PII? +
It doesn't just scan for keywords; it flags endpoints that are categorized as exposing regulated data flows, like names and emails (PII). This gives you a precise map of where the sensitive data leaves your system.
Can I find shadow APIs using list_catalog_endpoints? +
Yes. list_catalog_endpoints specifically identifies all discovered endpoints, including 'shadow' or zombie APIs that are running but haven't been properly documented or decommissioned.
What is the difference between list_vulnerabilities and get_vulnerability? +
list_vulnerabilities gives you a summary list of all current security flaws across your applications. You then use get_vulnerability to drill down, retrieving detailed diagnostic evidence for one specific flaw.
Is export_openapi_spec accurate? +
It's highly accurate because it generates the specification based on real-time observed traffic. This means your documentation matches what users and services are actually calling right now.
How does running `list_environments` help me scope my audit? +
It lists all deployment boundaries monitored by Levo sensors. You can quickly see if your API is actively tracked across staging, development, or production environments without manually checking every service.
If I run `get_observation`, what kind of anomalous data do I get? +
You receive specific details on a single runtime anomaly. This lets you see exactly what triggered the alert—for instance, unexpected schema drift or unusual traffic patterns that deviate from the baseline.
Why use `get_endpoint_details` instead of just listing endpoints? +
It returns the deep, full schema structure for a single API endpoint. This is critical when you need to verify precise request and response data types that simple listings don't capture.
What does `get_vulnerability` show me about an exploit? +
It provides detailed diagnostic exploitation evidence for a specific vulnerability. Instead of just naming the flaw, you get the root cause analysis and steps needed to remediate it.
Can Levo.ai identify undocumented APIs in my environment? +
Yes. Use the list_catalog_endpoints tool to see the full inventory auto-discovered by Levo sensors. Your agent can highlight 'Shadow' or 'Zombie' APIs that exist in your infrastructure but are missing from official documentation.
How do I check which endpoints are exposing PII or sensitive data? +
The list_sensitive_data tool allows your agent to query endpoints categorized by regulated data flows. You'll see which paths are transmitting names, emails, SSNs, or financial data, helping you prioritize compliance audits.
Can my agent generate a live OpenAPI specification for an existing service? +
Absolutely. Use the export_openapi_spec tool with a specific App ID. Your agent will retrieve a specification derived from actual observed traffic, providing a more accurate reflection of your live API than static files.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
More in this category
Aliyun OSS / 阿里云对象存储
China's leading object storage service — manage files, buckets, and metadata via AI.
Yodiz
Manage user stories, sprints, bugs, and epics on Yodiz — the all-in-one agile project management and issue tracking tool.
Keywords AI
Monitor and optimize your LLM API usage with a unified gateway that tracks costs, latency, and model performance across providers.
You might also like
Portkey
AI gateway observability: monitor logs, costs, and manage LLM configurations via agents.
Metatext
No-code NLP and AI model management via Metatext — run inference and manage datasets.
Unbounce
Build high-converting landing pages with AI-powered optimization that tests headlines, copies, and layouts automatically.