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Precog

Precog is an enterprise AI platform that acts as a "context engine" — turning fragmented, context-stripped data from SaaS applications and databases into live semantic layers that business users can query in natural language through AI assistants like Claude and ChatGPT. Its Intelligent Ingest builds no-code ETL pipelines from any business application into a data warehouse, detecting data relationships automatically and injecting business logic, definitions and relationships during ingestion, while its AI Assistants layer adds source tracing and SQL visibility for trustworthy answers. Precog exposes a public HTTP REST API (sources, destinations, pipelines, datasets, semantic-model generation) and an OAuth-secured Model Context Protocol (MCP) server, and was surfaced through the Techstars portfolio into the API Evangelist network.

agent native

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.

Kin Score

API Evangelist profiles Precog the way a machine reads it — 20 machine-readable artifacts across 12 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 — Precog scores 49.1/100 (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.

Kin Score Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5
Composite quality — 49.1/100 · developing
Contract Quality 15.0 / 25
Developer Ergonomics 10.0 / 20
Commercial Clarity 12.1 / 20
Operational Transparency 2.1 / 13
Governance 0.0 / 12
Discoverability 10.0 / 10
Agent readiness — 72/100 · agent native
Machine-Readable Contract 18 / 18
Agentic Access Contract 15 / 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 5 / 5
Well-Known Catalog 4 / 4
Consent & Bot Identity 3 / 3

How we profile Precog

Each block below is one kind of artifact we hold for Precog. 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 12

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.

Precog Admin API

The Admin API from Precog — 4 operation(s) for admin.

Precog Data Model API

The Data Model API from Precog — 1 operation(s) for data model.

Precog Datasets API

The Datasets API from Precog — 1 operation(s) for datasets.

Precog Destinations API

The Destinations API from Precog — 2 operation(s) for destinations.

Precog Issues API

The Issues API from Precog — 4 operation(s) for issues.

Precog Kinds API

The Kinds API from Precog — 3 operation(s) for kinds.

Precog Loads API

The Loads API from Precog — 1 operation(s) for loads.

Precog Log API

The Log API from Precog — 1 operation(s) for log.

Precog Pipelines API

The Pipelines API from Precog — 18 operation(s) for pipelines.

Precog Semantic Model API

The Semantic Model API from Precog — 3 operation(s) for semantic model.

Precog Sources API

The Sources API from Precog — 6 operation(s) for sources.

Precog Stripe API

The Stripe API from Precog — 2 operation(s) for stripe.

Scroll within the panel for all 12 ·

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.

precog-mcp.yml

MCP SERVER

JSON Schema 1

Standalone JSON Schema definitions describe the data models behind the API. We profile them so the shapes are validatable on their own — useful long after a single request is forgotten.

Standalone JSON Schema definitions for this provider's data models.

Foundation Semantic Model

3 properties

JSON SCHEMA

Security 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.

Precog Authentication

http/oauth2 · 2 schemes

SECURITY

Precog Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Precog Vulnerability Disclosure

security.txt · contact published

SECURITY

Precog Trust Center

SOC 2 Type II

SECURITY

Scopes 1

OAuth scopes are the vocabulary of least-privilege access. Profiling them shows exactly what an integration — or an agent acting on a user's behalf — is allowed to do.

OAuth scopes governing access to this provider's APIs.

Precog Scopes

3 scopes · authorizationCode/clientCredentials

3 scopes

SCOPES

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.

Precog Agentic Access

62 operations · 35 acting · 4 human-in-the-loop

62 operations · 35 acting

AGENTIC

Resources

Every other property we hold for Precog — 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 2

Portal, sign-up, and the first successful call

Documentation 1

Reference material describing how the API behaves

Design & Contract 4

Pagination, idempotency, versioning, errors, and events

Build 1

SDKs, sample code, and the tooling you integrate with

Operate 1

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 3

Properties that don't map to a standard resource type

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