Anam
Anam builds real-time, interactive AI avatars — photorealistic conversational personas that hold face-to-face video conversations for customer support, sales, tutoring, medical and training use cases. Its CARA avatar engine streams over WebRTC with sub-200ms latency and 70+ languages, fronted by a REST API (api.anam.ai) for managing personas, avatars, voices, LLM routing, knowledge (RAG) groups, function-calling tools, session tokens, share links and session analytics. Developers integrate via first-party JavaScript and Python SDKs, a Kotlin Multiplatform SDK, and a Pipecat plugin, or embed a no-code widget. Anam is a Redpoint Ventures portfolio company.
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 Anam the way a machine reads it — 15 machine-readable artifacts across 9 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 — Anam scores 57.4/100 (developing), with a separate agent-readiness read of 72/100 (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 Anam
Each block below is one kind of artifact we hold for Anam. 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 9
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.
Anam Auth API
The Auth API from Anam — 1 operation(s) for auth.
Anam Avatars API
The Avatars API from Anam — 2 operation(s) for avatars.
Anam Knowledge API
The Knowledge API from Anam — 5 operation(s) for knowledge.
Anam Llms API
The Llms API from Anam — 2 operation(s) for llms.
Anam Personas API
The Personas API from Anam — 2 operation(s) for personas.
Anam Sessions API
The Sessions API from Anam — 2 operation(s) for sessions.
Anam Share Links API
The Share Links API from Anam — 2 operation(s) for share links.
Anam Tools API
The Tools API from Anam — 2 operation(s) for tools.
Anam Voices API
The Voices API from Anam — 2 operation(s) for voices.
Scroll within the panel for all 9 ·
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.
anam-mcp.yml
MCP SERVERSecurity Posture 4
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 Anam — 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 3
Reference material describing how the API behaves
Agent Surfaces 5
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 5
Pagination, idempotency, versioning, errors, and events
Build 3
SDKs, sample code, and the tooling you integrate with
Access & Security 7
Authentication, authorization, and security posture
Scroll within the panel for all 7 ·
Operate 3
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
Other 1
Properties that don't map to a standard resource type
← All providers · Data indexed from github.com/api-evangelist/anam · machine-readable index on apis.io