Compatible with every major AI agent and IDE
Create annotation on Axiom
Create a new annotation
Create dashboard on Axiom
Create a new dashboard
Create dataset on Axiom
Create a new dataset
Create monitor on Axiom
Create a new monitor
Create notifier on Axiom
Create a new notifier
Delete annotation on Axiom
Delete an annotation
Delete dashboard on Axiom
Delete a dashboard
Delete dataset on Axiom
Delete a dataset
Delete monitor on Axiom
Delete a monitor
Delete notifier on Axiom
Delete a notifier
Get annotation on Axiom
Retrieve a specific annotation by ID
Get dashboard on Axiom
Retrieve a specific dashboard by UID
Get dataset on Axiom
Retrieve a specific dataset by ID
Get monitor on Axiom
Retrieve a specific monitor by ID
Get notifier on Axiom
Retrieve a specific notifier by ID
Get org on Axiom
Retrieve an organization by ID
Get user on Axiom
Retrieve a specific user by ID
Ingest data on Axiom
Ingest data into an Axiom dataset
List annotations on Axiom
List all annotations
List dashboards on Axiom
List all dashboards
List datasets on Axiom
List all datasets
List monitors on Axiom
List all monitors
List notifiers on Axiom
List all notifiers
List tokens on Axiom
List all API tokens
List users on Axiom
List all users
Run query on Axiom
Run an APL query against Axiom data
Update annotation on Axiom
Update an existing annotation
Update dashboard on Axiom
Update an existing dashboard
Update dataset on Axiom
Update an existing dataset
Update monitor on Axiom
Update an existing monitor
Update notifier on Axiom
Update an existing notifier
How Vinkius protects your data
What happens if the underlying API rate limits my agent?
Our edge infrastructure automatically handles backoffs, queueing, and throttling. If an AI agent sends too many erratic requests, Vinkius manages the rate limits gracefully, ensuring your backend doesn't crash.
Can I run complex log analysis using Axiom Processing Language (APL)?
Yes! Use the run_query tool to execute any APL string. You can specify start_time and end_time to filter your data and get precise analytical results directly in the chat.
What if the AI ends up reading customer data or confidential information?
We have a built-in digital "bodyguard" called DLP (Data Loss Prevention). If a tool fetches data and the response contains social security numbers, credit cards, or personal customer info, Vinkius magically blocks and erases that information before it is delivered to the AI. The AI works only with what is strictly necessary, and your sensitive data never leaks.
Does the AI train on my tools or API data?
No. Vinkius enforces a strict Zero-Retention policy. Your data simply passes through our secure servers to complete the requested action and is instantly forgotten. Nothing you do here is ever stored, logged, or used to train any artificial intelligence.
What can AI Agents do with Axiom?
Integrate Axiom to provide your custom AI agents with direct read and write access to the capabilities listed below.
Next-Gen telemetry Automation
Integrate Axiom for AI-driven telemetry management. The MCP server structures the outputs required for Claude to analyze data analytics data.
AI-Driven log analysis Workflows
The Axiom MCP manages API routing for log analysis. This enables AI agents like Claude Code to execute structured data analytics queries.
Axiom. Runs on everything.
From IDE to framework. Every connection governed by Vinkius.
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
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