Maia-analytics
MAIA Analytics is an AI-powered geospatial analysis platform that lets anyone turn complex location data into actionable insights through natural-language queries, with no GIS degree required. It unifies open and proprietary data to reveal the built environment and supports use cases such as solar-site prospecting, building and parcel analysis, redevelopment and risk screening (flood zones, aging infrastructure), and location intelligence. Every answer is source-linked and verifiable. Founded in 2023 and backed by Homebrew. This profile was enriched from MAIA's public site and its publicly-served backend OpenAPI (the application's own FastAPI backend; MAIA does not publish an external developer program).
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 Maia-analytics the way a machine reads it — 37 machine-readable artifacts across 33 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 — Maia-analytics scores 38.7/100 (thin), with a separate agent-readiness read of 74/100 (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
How this is scored →scored 2026-07-27 · rubric v0.5
How we profile Maia-analytics
Each block below is one kind of artifact we hold for Maia-analytics. 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 33
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.
Maia-analytics Ah API
The Ah API from Maia-analytics — 1 operation(s) for ah.
Maia-analytics analytics API
The analytics API from Maia-analytics — 1 operation(s) for analytics.
Maia-analytics audit-log API
The audit-log API from Maia-analytics — 1 operation(s) for audit-log.
Maia-analytics auth API
The auth API from Maia-analytics — 8 operation(s) for auth.
Maia-analytics chat API
The chat API from Maia-analytics — 8 operation(s) for chat.
Maia-analytics dial API
The dial API from Maia-analytics — 8 operation(s) for dial.
Maia-analytics enrichment API
The enrichment API from Maia-analytics — 17 operation(s) for enrichment.
Maia-analytics example-projects API
The example-projects API from Maia-analytics — 9 operation(s) for example-projects.
Maia-analytics favorite API
The favorite API from Maia-analytics — 2 operation(s) for favorite.
Maia-analytics feature-flags API
The feature-flags API from Maia-analytics — 3 operation(s) for feature-flags.
Maia-analytics filters API
The filters API from Maia-analytics — 1 operation(s) for filters.
Maia-analytics geographies API
The geographies API from Maia-analytics — 1 operation(s) for geographies.
Maia-analytics internal API
The internal API from Maia-analytics — 50 operation(s) for internal.
Maia-analytics internal-knowledge API
The internal-knowledge API from Maia-analytics — 4 operation(s) for internal-knowledge.
Maia-analytics internal-projects API
The internal-projects API from Maia-analytics — 1 operation(s) for internal-projects.
Maia-analytics internal-skills API
The internal-skills API from Maia-analytics — 4 operation(s) for internal-skills.
Maia-analytics knowledge API
The knowledge API from Maia-analytics — 2 operation(s) for knowledge.
Maia-analytics layer API
The layer API from Maia-analytics — 3 operation(s) for layer.
Maia-analytics MAIA API API
The MAIA API API from Maia-analytics — 1 operation(s) for maia api.
Maia-analytics map API
The map API from Maia-analytics — 4 operation(s) for map.
Maia-analytics notes API
The notes API from Maia-analytics — 2 operation(s) for notes.
Maia-analytics project API
The project API from Maia-analytics — 15 operation(s) for project.
Maia-analytics project-lock API
The project-lock API from Maia-analytics — 2 operation(s) for project-lock.
Maia-analytics query API
The query API from Maia-analytics — 1 operation(s) for query.
Maia-analytics saved-contacts API
The saved-contacts API from Maia-analytics — 7 operation(s) for saved-contacts.
Maia-analytics share API
The share API from Maia-analytics — 17 operation(s) for share.
Maia-analytics skills API
The skills API from Maia-analytics — 2 operation(s) for skills.
Maia-analytics stats API
The stats API from Maia-analytics — 1 operation(s) for stats.
Maia-analytics table API
The table API from Maia-analytics — 12 operation(s) for table.
Maia-analytics user-events API
The user-events API from Maia-analytics — 1 operation(s) for user-events.
Maia-analytics users API
The users API from Maia-analytics — 7 operation(s) for users.
Maia-analytics workspace API
The workspace API from Maia-analytics — 9 operation(s) for workspace.
Maia-analytics workspaces API
The workspaces API from Maia-analytics — 18 operation(s) for workspaces.
Scroll within the panel for all 33 ·
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.
maia-analytics-mcp.yml
MCP SERVERSecurity Posture 2
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 Maia-analytics — 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 1
Portal, sign-up, and the first successful call
Documentation 2
Reference material describing how the API behaves
Agent Surfaces 4
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 6
Pagination, idempotency, versioning, errors, and events
Build 1
SDKs, sample code, and the tooling you integrate with
Access & Security 2
Authentication, authorization, and security posture
Commercial 2
Pricing, plans, and the legal terms of use
Company 1
The organization behind the API
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