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Sema4 Ai

Sema4.ai is an enterprise AI agent company building a platform that lets organizations design, run, and manage AI agents that combine actions, intelligence, and enterprise context to transform knowledge work. Its developer surface centers on AI Actions — Python functions exposed to agents via the open-source Sema4.ai Action Server, which serves both an OpenAPI-compatible REST API and a Model Context Protocol (MCP) server. The platform adds a versioned REST API (v2) for driving agents, conversations, Work Items, data connections, MCP servers, and audits programmatically, plus Enterprise and Snowflake-native Team editions. Founded by the team behind Robocorp, Sema4.ai is backed by Mayfield.

agent aware

Limited machine-readable signal and partial portal coverage — documentation a human can read, but little a machine or agent can consume without scraping.

Kin Score

API Evangelist profiles Sema4 Ai the way a machine reads it — 5 machine-readable artifacts across 1 API, 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 — Sema4 Ai scores 37.1/100 (thin), with a separate agent-readiness read of 36/100 (agent aware). 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 Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5
Composite quality — 37.1/100 · thin
Contract Quality 0.0 / 25
Developer Ergonomics 14.8 / 20
Commercial Clarity 8.9 / 20
Operational Transparency 4.1 / 13
Governance 0.0 / 12
Discoverability 9.3 / 10
Agent readiness — 36/100 · agent aware
Machine-Readable Contract 0 / 18
Agentic Access Contract 0 / 15
MCP Server 12 / 12
Machine-Readable Auth 10 / 10
Idempotency 0 / 9
Stable Error Semantics 8 / 8
Request/Response Examples 0 / 7
Rate-Limit Signaling 0 / 7
Typed Event Surface 0 / 6
Agent Skills 0 / 5
Well-Known Catalog 4 / 4
Consent & Bot Identity 3 / 3

How we profile Sema4 Ai

Each block below is one kind of artifact we hold for Sema4 Ai. 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 1

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.

Sema4.ai REST API

The v2 REST API drives the Sema4.ai platform programmatically — list and talk to agents, stream responses, queue and manage Work Items, read data connections, manage MCP servers...

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.

sema4-ai-mcp.yml

MCP SERVER

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.

Sema4 Ai Authentication

http/openIdConnect · 3 schemes

SECURITY

Sema4 Ai Domain Security

TLSv1.3 · HSTS · DNSSEC · DMARC

SECURITY

Sema4 Ai Vulnerability Disclosure

security.txt · contact published

SECURITY

Resources

Every other property we hold for Sema4 Ai — 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 3

MCP servers, agent skills, and machine-readable catalogs

Build 4

SDKs, sample code, and the tooling you integrate with

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

← All providers · Data indexed from github.com/api-evangelist/sema4-ai · machine-readable index on apis.io