TawkitAI
CopilotKit (built by TawkitAI Inc., a Techstars Seattle '23 company) is an open-source, enterprise-grade agentic frontend framework for embedding AI copilots and agents directly into web and mobile applications. It provides React, Angular, Vue and React Native SDKs, prebuilt and headless chat UI components (CopilotChat, CopilotSidebar, CopilotPopup, CopilotTextarea), a GraphQL-based Copilot Runtime, a Python agent SDK, and the AG-UI protocol — a bi-directional connection between a user-facing app and any agentic backend (LangGraph, CrewAI, PydanticAI, Mastra, AWS Strands and others). Copilot Cloud is the hosted platform, adding thread and state persistence, generative UI, and multi-channel delivery across web, mobile, Slack, Teams and WhatsApp. The core is MIT-licensed (github.com/CopilotKit/CopilotKit, ~34.5k stars).
Limited machine-readable signal and partial portal coverage — documentation a human can read, but little a machine or agent can consume without scraping.
API Evangelist profiles TawkitAI the way a machine reads it — 3 machine-readable artifacts, 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 — TawkitAI scores 34.9/100 (thin), with a separate agent-readiness read of 10/100 (human only). 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.
Kin Score
How this is scored →scored 2026-07-27 · rubric v0.5
How we profile TawkitAI
Each block below is one kind of artifact we hold for TawkitAI. 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.
Security 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.
Resources
Every other property we hold for TawkitAI — 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 2
Reference material describing how the API behaves
Agent Surfaces 1
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 4
Pagination, idempotency, versioning, errors, and events
Build 4
SDKs, sample code, and the tooling you integrate with
Access & Security 4
Authentication, authorization, and security posture
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
← All providers · Data indexed from github.com/api-evangelist/tawkitai · machine-readable index on apis.io