Expected Parrot

Expected Parrot is a research-technology company building tools for AI-powered social science. Its open-source Python library EDSL (Expected Parrot Domain-Specific Language) lets researchers design, conduct, and analyze surveys and experiments in which large language models power simulated AI agents that answer questions, alongside or in place of human respondents. The Expected Parrot platform adds remote inference across many model providers (Anthropic, OpenAI, Google, Mistral, and more) via a single Expected Parrot API key, plus cloud storage, sharing, and collaboration for surveys, agents, scenarios, and results. It is used for market research, data labeling, digital twins, synthetic-user UX studies, and reproducible computational social science.

Expected Parrot is profiled on the APIs.io network. Tagged areas include Company, Artificial Intelligence, Large Language Models, Surveys, and Research.

Expected Parrot’s developer surface includes documentation, getting-started guide, pricing, authentication, changelog, and 8 more developer resources.

🌐 Visit website 📡 Source on GitHub

22.9/100 emerging ▬ flat Agent 14/100 human only Full breakdown ↓
scored 2026-07-27 · rubric v0.5

AccessSelf serve

0 APIs

CompanyArtificial IntelligenceLarge Language ModelsSurveysResearchSocial ScienceSynthetic DataAI AgentsMarket ResearchPython

Kin Score

Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5

Composite quality — 22.9/100 · emerging

Contract Quality 0.0 / 25

Developer Ergonomics 8.7 / 20

Commercial Clarity 4.7 / 20

Operational Transparency 2.7 / 13

Governance 0.0 / 12

Discoverability 6.8 / 10

Agent readiness — 14/100 · human only

Machine-Readable Contract 0 / 18

Agentic Access Contract 0 / 15

MCP Server 0 / 12

Machine-Readable Auth 10 / 10

Idempotency 0 / 9

Stable Error Semantics 0 / 8

Request/Response Examples 0 / 7

Rate-Limit Signaling 0 / 7

Typed Event Surface 0 / 6

Agent Skills 5 / 5

Well-Known Catalog 0 / 4

Consent & Bot Identity 0 / 3

Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. This rating is computed from github.com/api-evangelist/expected-parrot: open an issue to ask a question, or submit a pull request to add artifacts. Want it done for you? Prioritized profiling — $2,500 →

Get Started 2

Portal, sign-up, and the first successful call

GettingStarted

GettingStarted

Login

Documentation 1

Reference material describing how the API behaves

Documentation

Documentation

Agent Surfaces 2

MCP servers, agent skills, and machine-readable catalogs

LLMsTxt

LLMsTxt

AgentSkill

AgentSkill

Build 3

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

GitHubOrganization

Packages

Packages

SDKs

SDKs

Access & Security 2

Authentication, authorization, and security posture

Authentication

Authentication

DomainSecurity

DomainSecurity

Operate 1

Status, limits, changes, and where to get help

ChangeLog

ChangeLog

Commercial 1

Pricing, plans, and the legal terms of use

Pricing

Pricing

Company 1

The organization behind the API

Website

Website

Source (apis.yml)

aid: expected-parrot
name: Expected Parrot
description: Expected Parrot is a research-technology company building tools for AI-powered social science. Its open-source
  Python library EDSL (Expected Parrot Domain-Specific Language) lets researchers design, conduct, and analyze surveys and
  experiments in which large language models power simulated AI agents that answer questions, alongside or in place of human
  respondents. The Expected Parrot platform adds remote inference across many model providers (Anthropic, OpenAI, Google,
  Mistral, and more) via a single Expected Parrot API key, plus cloud storage, sharing, and collaboration for surveys, agents,
  scenarios, and results. It is used for market research, data labeling, digital twins, synthetic-user UX studies, and reproducible
  computational social science.
url: https://raw.githubusercontent.com/api-evangelist/expected-parrot/refs/heads/main/apis.yml
accessModel:
  pricing: unknown
  onboarding: self-serve
  trial: false
  try_now: false
  public: false
  label: Self-serve signup
  confidence: medium
  source:
  - authentication
  generated: '2026-07-22'
  method: derived
image: https://github.com/expectedparrot.png
x-type: company
x-source: vc-portfolio
x-backed-by:
- bloomberg-beta
- y-combinator
x-tier: stub
x-tier-reason: portfolio-lead
specificationVersion: '0.20'
created: '2026-07-17'
modified: '2026-07-19'
tags:
- Company
- Artificial Intelligence
- Large Language Models
- Surveys
- Research
- Social Science
- Synthetic Data
- AI Agents
- Market Research
- Python
apis: []
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Website
  url: https://www.expectedparrot.com/
- type: Documentation
  url: https://docs.expectedparrot.com/
- type: GettingStarted
  url: https://docs.expectedparrot.com/en/latest/getting_started.html
- type: GitHubOrganization
  url: https://github.com/expectedparrot
- type: Pricing
  url: https://www.expectedparrot.com/models
- type: Login
  url: https://www.expectedparrot.com/login
- type: Packages
  url: packages/expected-parrot-packages.yml
- type: SDKs
  url: packages/expected-parrot-packages.yml
- type: Authentication
  url: authentication/expected-parrot-authentication.yml
- type: ChangeLog
  url: changelog/expected-parrot-changelog.yml
- type: LLMsTxt
  url: llms/expected-parrot-llms.txt
- type: AgentSkill
  url: skills/_index.yml
- type: DomainSecurity
  url: security/expected-parrot-domain-security.yml
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence