Panther
Panther is a cloud-native, code-driven detection and response platform and AI-powered SOC that ingests and normalizes security logs at petabyte scale into a security data lake (customer-connected AWS/Snowflake/Databricks or Panther-hosted). It offers Python detection-as-code, AI-generated detections, correlation and scheduled rules, cloud-security policies, and an AI SOC agent that auto-triages and investigates alerts. Developers automate it through a REST API (X-API-Key), a GraphQL API, Terraform, the panther_analysis_tool CLI, and official local and remote MCP servers. Backed by ICONIQ Capital and Lightspeed Venture Partners.
Real signal across most facets with visible, nameable gaps — the contract exists but is thin, or the portal is good while governance and commercial terms are absent.
API Evangelist profiles Panther the way a machine reads it — 27 machine-readable artifacts across 21 APIs, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — Panther scores 54.6/100 (developing), with a separate agent-readiness read of 67/100 (agent native). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Kin Score
This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.
How we profile Panther
Each block below is one kind of artifact we hold for Panther. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.
APIs 21
Each API is captured as its own OpenAPI definition — every operation, parameter, and response. This is the single most useful machine-readable description of what an API does, and it's what lets us score, lint, mock, and generate against it without asking the provider for anything.
Individual APIs this provider publishes, each with its own machine-readable definition.
Panther alert API
The alert api handles all operations for alerts
Panther api token API
The api token api handles all operations for api tokens
Panther aws cloud account API
The AWS Cloud Account API handles all operations for AWS Cloud Account scanner integrations
Panther comment API
The comment api handles all operations for alerts comments
Panther contexttag API
The context tag API handles all operations for alert context tags
Panther correlation rule API
The correlation rule api handles all operations for correlation rules
Panther data model API
The data model api handles all operations for data models
Panther gcs source API
The GCS source API handles all operations for Google Cloud Storage log sources
Panther global API
The global api handles all operations for globals
Panther http source API
The http source api handles all operations for http sources
Panther log forwarder source API
The log forwarder source api handles all operations for log forwarder sources
Panther log source alarm API
Manage the drop-off alarm (SOURCE_NO_DATA) for log source integrations. Other alarm types shown in the Panther UI (permissions checks, classification failures, log-processing er...
Panther policy API
The policy api handles all operations for policies
Panther pub/sub source API
The Pub/Sub source API handles all operations for GCP Pub/Sub log sources
Panther query API
The query api handles operations for queries
Panther role API
The role api handles all operations for roles
Panther rule API
The rule api handles all operations for rules
Panther s3 source API
The S3 source API handles all operations for AWS S3 log sources
Panther scheduled rule API
The scheduled rule api handles all operations for scheduled rules
Panther simple rule API
The simple rule api handles all operations for simple rules
Panther user API
The user api handles all operations for users
Scroll within the panel for all 21 ·
MCP Servers 1
Model Context Protocol servers expose these APIs directly to AI agents. We profile them because agent-native access is the fastest-growing way this provider's capabilities actually get used.
Model Context Protocol servers that expose these APIs to AI agents.
panther-mcp.yml
MCP SERVEREvent Specifications 1
Not every API is request/response. AsyncAPI describes the event-driven and streaming side — the webhooks and channels — so the asynchronous half of the interface is documented the same way the synchronous half is.
AsyncAPI definitions for this provider's event-driven and streaming APIs.
Panther Webhooks
ASYNCAPISecurity Posture 3
Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Agentic Access 1
An x-agentic-access contract marks which operations are safe for an agent to run on its own and which need a human in the loop. It is the difference between an API an agent can use and one it can use safely.
Recommended x-agentic-access execution contracts for AI agents.
Resources
Every other property we hold for Panther — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.
Get Started 3
Portal, sign-up, and the first successful call
Documentation 1
Reference material describing how the API behaves
Agent Surfaces 5
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 4
Pagination, idempotency, versioning, errors, and events
Build 3
SDKs, sample code, and the tooling you integrate with
Access & Security 4
Authentication, authorization, and security posture
Operate 2
Status, limits, changes, and where to get help
Commercial 3
Pricing, plans, and the legal terms of use
Company 2
The organization behind the API
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