Read AI is an AI-powered meeting intelligence platform that joins Zoom, Microsoft Teams and Google Meet calls as an authorized notetaker and turns them into structured meeting reports — summaries, chapter summaries, action items, key questions, topics, full speaker-attributed transcripts and engagement metrics — plus enterprise search across email, messaging and calendar. Founded in 2021 in Seattle by the team behind Placed and Foursquare, it reports more than five million monthly active users. For developers, Read AI ships an open-beta public REST API at api.read.ai (v1 meetings, live meetings, cursor pagination, expandable fields), a remote Model Context Protocol server at api.read.ai/mcp listed in the Anthropic and ChatGPT connector directories, HMAC-signed user and workspace webhooks, three provider-authored downloadable Agent Skills, and an OAuth 2.1 authorization server with dynamic client registration. It publishes no OpenAPI.
Read AI publishes 2 APIs on the APIs.io network. Tagged areas include Company, Meeting Intelligence, Artificial Intelligence, Transcription, and Productivity.
The Read AI catalog on APIs.io includes 1 event-driven AsyncAPI specification.
Read AI’s developer surface includes documentation, API reference, getting-started guide, support, engineering blog, pricing, signup flow, and 25 more developer resources.
Regulatory Posture applies to this provider. Its tags matched the
Horizontal (data, software, accessibility, platform) regime, so
Regulatory Posture carries 15 points of the composite.
If this regime is wrong for your business, say so on your
provider repo — the
applicability map is public and we will correct it.
Create-or-Update Ergonomics could not be measured. We hold no machine-readable contract for
this provider to read, so there is nothing to measure a write surface against. Excluded rather than scored zero:
never-measured and measured-empty are different facts. Publishing an OpenAPI is what makes this facet — and
several others — scorable at all.
The six quality facets above are damped to 85 points between them,
because the conditional facet above carries the other
15. That is why each facet's contribution is shown against a damped
maximum: raising a quality facet moves the composite by 85% of its nominal
weight, not 100%. The full arithmetic is at apis.io/rating/.
Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. Every facet and dimension name above is a link: it opens that measurement's own page — what it means, the exact checks that feed it, how the whole catalog distributes on it, and the providers at the top of it. This rating is computed from github.com/api-evangelist/read-ai: open an issue to ask a question, or submit a pull request to add artifacts.
Submit an artifact on GitHub — free →Manage your own listing — the Influence plan, $499/mo →
Open-beta public REST API for programmatic access to a user's Read AI meeting data. Three documented meeting endpoints — list meetings with cursor pagination and epoch-milliseco...
First-party remote Model Context Protocol server exposing a user's Read AI meeting reports to any MCP client over Streamable HTTP. Two published tools — list_meetings and get_me...
Read AI operates a first-party remote MCP server that exposes a user's meeting reports — metadata, participants, summaries, chapter summaries, action items, key questions, topic...
Discovery needs no key. Ratings and market analysis are Pro.
Get an API key
Free tier, no form to fill in. Signing in shares your email address with us — we
store it to create your key and to recognise you if you sign in with another
provider. See our Privacy Policy and
Terms.