Screenpipe
Screenpipe is a local-first, source-available desktop application (by Mediar AI, Y Combinator S26) that continuously captures everything you see, say, and hear on your computer, reads on-screen text through OS accessibility APIs with an OCR fallback, transcribes system and microphone audio locally with Whisper, and stores it all in a local SQLite database as a private, searchable memory. It exposes a full local REST API at http://localhost:3030 (71 operations across search, frames, audio, meetings, memories, speakers, tags, vault, cloud sync, cloud archive, and data retention) and ships as an MCP server so agents like Claude, Cursor, Codex, and Cline can query screen history and meeting transcripts. Automations are built as "pipes" — scheduled AI agents written in plain markdown. It is positioned as an open, local-first alternative to Rewind.ai, Microsoft Recall, and cloud meeting bots.
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.
API Evangelist profiles Screenpipe the way a machine reads it — 24 machine-readable artifacts across 18 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 — Screenpipe scores 45.0/100 (developing), with a separate agent-readiness read of 65/100 (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 Screenpipe
Each block below is one kind of artifact we hold for Screenpipe. 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 18
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.
Screenpipe Activity API
Activity summaries and analytics
Screenpipe Audio API
Manage audio recording devices
Screenpipe Cloud Archive API
Archive old data to cloud storage
Screenpipe Cloud Sync API
Sync data across devices via cloud
Screenpipe Data Management API
Manual data deletion and storage info
Screenpipe Data Retention API
Auto-delete old data locally
Screenpipe Database API
Direct database access
Screenpipe Elements API
Query captured UI accessibility tree data
Screenpipe Experimental API
Experimental/unstable endpoints
Screenpipe Frames API
Access captured screenshots and their extracted text
Screenpipe Meetings API
Detected and manual meeting transcriptions
Screenpipe Memories API
AI-extracted knowledge from screen activity
Screenpipe Search API
Search through captured screen and audio content
Screenpipe Speakers API
Speaker identification and management
Screenpipe System API
Health checks and system status
Screenpipe Tags API
Tag content items for organization
Screenpipe Vault API
Encrypt/decrypt all data at rest
Screenpipe Vision API
Manage screen capture monitors
Scroll within the panel for all 18 ·
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.
screenpipe-mcp.yml
MCP SERVERSecurity 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.
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 Screenpipe — 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 4
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 5
Pagination, idempotency, versioning, errors, and events
Build 4
SDKs, sample code, and the tooling you integrate with
Access & Security 6
Authentication, authorization, and security posture
Operate 5
Status, limits, changes, and where to get help
Commercial 1
Pricing, plans, and the legal terms of use
Company 1
The organization behind the API
← All providers · Data indexed from github.com/api-evangelist/screenpipe · machine-readable index on apis.io