reviewpaper-ai

ReviewPaper.ai is an AI-powered platform that generates peer‑review style feedback for academic papers submitted to major conferences such as NeurIPS, ICLR, and ACL. By simulating the exact review format of each venue, it provides a predicted score, a ranked list of suggested improvements, and the ability to iteratively re‑review revised drafts or draft rebuttals. The service offers three free reviews per user and aims to help researchers strengthen their submissions before official review.

reviewpaper-ai is listed with 1 API on the APIs.io network. Tagged areas include AI, Peer Review, Academic, NLP, and Research Tools.

reviewpaper-ai’s developer surface includes documentation, getting-started guide, pricing, and 12 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

28.1/100 thin Agent 18/100 agent aware Full breakdown ↓
scored 2026-10-31 · rubric v0.25.0 · Show this score on your site →

1 API 1 MCP Servers

AIPeer ReviewAcademicNLPResearch Tools

Kin Score

Kin Score How this is scored →
scored 2026-10-31 · rubric v0.25.0

Composite quality — 28.1/100 · thin

Contract Quality 0.0 / 21

Developer Ergonomics 3.6 / 17

Access Clarity 13.0 / 17

Operational Transparency 0.6 / 11

Contract Governance 1.9 / 10

Discoverability 4.8 / 9

Regulatory Posture 2.7 / 15

Agent readiness — 18/100 · agent aware

Machine-Readable Contract 0 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 12 / 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 0 / 5

Well-Known Catalog 0 / 4

Consent & Bot Identity 0 / 3

A2A Agent Card 0 / 8

Dry-Run / Simulate Mode 0 / 4

Delegated User Identity 6 / 6

Protected Resource Metadata 0 / 5

Registration Without a Human 6 / 6

Agentic Commerce Well-Known Document 0 / 5

Pagination 5 / 5

Distinct Operations 3 / 3

Regulatory Posture applies to this provider. Its tags matched the Education & Research 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/.

Show this score on your site.

It updates itself when the score changes. Paste this where you link to your API docs:

<a href="https://apis.io/providers/reviewpaper-ai/"><img src="https://apis.io/badge/reviewpaper-ai/card.svg" alt="reviewpaper-ai on APIs.io — Kin Score by API Evangelist"></a>

Other styles, a README pill and a shields.io endpoint are on the badge page.

Raise your score.

Agent readiness — checks not met, largest first (exact, from this profile):

Machine-Readable Contract +18 pts — api_specs includes an OpenAPI document
Agentic Access Contract +10 pts — agentic_access artifact present (x-agentic-access), graded by author
Idempotency +9 pts — OpenAPI mutating operations declare an idempotency key — a header, a request-body property, or a named de-duplication token whose own description says so (verified); else common[].type matches /idempoten/i (documented)
A2A Agent Card +8 pts — a2a/-a2a.yml manifest, graded on conformance.grade against A2A 1.0.0
Stable Error Semantics +8 pts — OpenAPI $refs a shared error schema across 4xx/5xx responses (verified), else common[].type includes ErrorCatalog / ErrorCodes / DeclineCodes
Rate-Limit Signaling +7 pts — OpenAPI responses document X-RateLimit-* / RateLimit headers (verified), else a rate_limits artifact or RateLimits link (documented)

9 more unmet checks in the Agent Readiness table above.

Kin Score — facets with the most composite points still available (weight × headroom):

Contract Quality scores 0.0 — up to +25.0 composite points
Developer Ergonomics scores 21.4 — up to +15.7 composite points
Operational Transparency scores 5.3 — up to +12.3 composite points

Each check links to what satisfies it. Publish the artifact, or tell us where it already lives, and the score moves on the next scoring run.

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 the provider profile at artifacts.apis.io/reviewpaper-ai/apis.yml: open an issue on github.com/api-evangelist/reviewpaper-ai to ask a question or point us at an artifact you publish. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

APIs 1

Individual APIs this provider publishes, each with its own machine-readable definition.

ReviewPaper AI API

Read‑only MCP server provides tools for AI agents to access venue review forms, deadlines, LLM policies, and other data.

MCP Servers 1

Model Context Protocol servers that expose these APIs to AI agents.

reviewpaper-ai MCP Server

Remote MCP server at reviewpaper.ai.

MCP SERVER

Pricing Plans 1

Published pricing tiers and plan structures.

Reviewpaper Ai Plans Pricing

3 plans

PLANS

Security Posture 2

Authentication, domain security, vulnerability disclosure, and trust-center signals.

Reviewpaper Ai Authentication

2 schemes

SECURITY

Reviewpaper Ai Domain Security

TLSv1.3 · HSTS

SECURITY

Resources

Get Started 2

Portal, sign-up, and the first successful call

Login

GettingStarted

GettingStarted

Documentation 1

Reference material describing how the API behaves

Documentation

Documentation

Agent Surfaces 3

MCP servers, agent skills, and machine-readable catalogs

LLMsTxt

LLMsTxt

MCPServer

MCPServer

WellKnown

WellKnown

Build 1

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

GitHubOrganization

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Commercial 4

Pricing, plans, and the legal terms of use

Plans

Pricing

TermsOfService

PrivacyPolicy

Company 1

The organization behind the API

Website

Website

Other 2

Properties that don't map to a standard resource type

Hosts

Hosts

Vendors

Vendors

Source (apis.yml)

aid: reviewpaper-ai
name: reviewpaper-ai
description: ReviewPaper.ai is an AI-powered platform that generates peer‑review style feedback for academic papers submitted
  to major conferences such as NeurIPS, ICLR, and ACL. By simulating the exact review format of each venue, it provides a
  predicted score, a ranked list of suggested improvements, and the ability to iteratively re‑review revised drafts or draft
  rebuttals. The service offers three free reviews per user and aims to help researchers strengthen their submissions before
  official review.
image: https://reviewpaper.ai/opengraph-image-pwu6ef?2656ec22fbde9d58
url: https://artifacts.apis.io/reviewpaper-ai/apis.yml
x-type: company
x-source: harvest:mcp-registry
x-tier: profiled
x-tier-reason: enrichment pass 2026-10-30 (modular-v1; was harvest)
specificationVersion: '0.20'
created: '2026-10-30'
modified: '2026-10-30'
tags:
- AI
- Peer Review
- Academic
- NLP
- Research Tools
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Plans
  url: plans/reviewpaper-ai-plans-pricing.yml
- type: LLMsTxt
  url: llms/reviewpaper-ai-llms.txt
- type: MCPServer
  url: mcp/reviewpaper-ai-mcp.yml
- type: WellKnown
  url: well-known/reviewpaper-ai-well-known.yml
- type: Hosts
  url: hosts/reviewpaper-ai-hosts.yml
- type: Vendors
  url: vendors/reviewpaper-ai-vendors.yml
- type: Login
  url: https://reviewpaper.ai/sign-in
- type: Documentation
  url: https://reviewpaper.ai/guides
- type: GettingStarted
  url: https://reviewpaper.ai/developers
- type: DomainSecurity
  url: security/reviewpaper-ai-domain-security.yml
- type: Website
  url: https://reviewpaper.ai/
- type: Pricing
  url: https://reviewpaper.ai/pricing
- type: TermsOfService
  url: https://reviewpaper.ai/terms
- type: PrivacyPolicy
  url: https://reviewpaper.ai/privacy
- type: GitHubOrganization
  url: https://github.com/reviewpaper-ai
apis:
- name: ReviewPaper AI API
  description: Read‑only MCP server provides tools for AI agents to access venue review forms, deadlines, LLM policies, and
    other data.
  humanURL: https://reviewpaper.ai/developers
  aid: reviewpaper-ai:reviewpaper-ai-api
x-coverage:
  state: unreadable
  reason: no-machine-readable-spec
  detail: Developer portal provides only a read‑only MCP server with no OpenAPI, GraphQL, or other machine‑readable contract.
  evidence:
  - url: https://reviewpaper.ai/developers
    status: 200
  checked: '2026-10-30'
x-enrichment:
  date: '2026-10-30'
  status: enriched
  artifacts_added: 11
  pass: modular-v1
  engine: identity=oss,contract=oss,surfaces=oss,docs=oss,regulatory=oss

reviewpaper-ai API — frequently asked questions

Does reviewpaper-ai have an API?

Yes. APIs.io lists 1 API from reviewpaper-ai, including ReviewPaper AI API.

How do I authenticate with the reviewpaper-ai API?

reviewpaper-ai documents its authentication (2 schemes). The details are profiled on APIs.io as Reviewpaper Ai Authentication.

How much does the reviewpaper-ai API cost?

APIs.io lists 3 pricing plans for reviewpaper-ai, with each plan's price, limits and inclusions under Pricing Plans on this page.

Does reviewpaper-ai have an MCP server?

Yes. APIs.io lists 1 MCP server for reviewpaper-ai: Remote MCP server at reviewpaper.ai.

Is the reviewpaper-ai API ready for AI agents?

reviewpaper-ai has a Kin Score of 28.1 out of 100 (thin) and an Agent Readiness score of 18.2 (agent-aware), scored by API Evangelist on 2026-10-31.

Work with this as data

Every provider here is available over the APIs.io API and to AI agents over MCP.

MCP server

One button, every client — Claude, Cursor, VS Code and the rest.

https://apis.io/mcp

Tools for providers

9 MCP tools reach this

find_providersBrowse and filter every provider in the catalog.
get_provider_artifactsEvery artifact this provider publishes, grouped by type.
get_provider_operationsEvery operation across all of their OpenAPIs — one call instead of parsing every spec.
get_provider_toolsEvery MCP tool they ship, with the operation each wraps.
get_provider_evidenceHow each part of their score was established. Free — the basis for a claim should not sit behind it.
get_provider_ratingPRO — composite, band, trend and facet scores.
apis_io_searchSTART HERE — APIs, providers and tags for one query, each with its total.
resolveTurn a domain, URL or GitHub org into the provider it belongs to.
find_cohortsEvery scored population of providers in the catalog.

All 92 tools →

Call it yourself

curl for this page

This provider

curl "https://apis.io/api/v1/providers/reviewpaper-ai"

All providers

curl "https://apis.io/api/v1/providers?limit=25"

Every operation they expose

curl "https://apis.io/api/v1/providers/reviewpaper-ai/operations?limit=25"

How their score was established

curl "https://apis.io/api/v1/providers/reviewpaper-ai/evidence"

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.

GitHub Google LinkedIn

A second provider on the same verified email joins the account you already have.