AI Arena

AI Arena is a web3/AI gaming company built by ArenaX Labs, backed by Paradigm and Framework Ventures. Its flagship title, AI Arena, is an Ethereum/Arbitrum-native PvP fighting game where players purchase, train through imitation learning, and battle characters powered by real artificial intelligence, with a native $NRN (Neuron) token and an on-chain marketplace for AI models. Beyond the game, ArenaX Labs ships developer infrastructure for reinforcement learning: RLMesh, an open-source, Gymnasium-compatible framework that connects RL models to environments across process, dependency, and machine boundaries over a gRPC wire protocol (rlmesh-wire-v1), with Python and Rust SDKs; and SAI (competesai.com), a gamified RL research and competition platform with its own CLI. This profile was enriched by the API Evangelist pipeline from public sources — GitHub, package registries, and the RLMesh documentation.

AI Arena is profiled on the APIs.io network. Tagged areas include Company, Gaming, Web3, Artificial Intelligence, and Reinforcement Learning.

AI Arena’s developer surface includes documentation, API reference, getting-started guide, engineering blog, CLI, changelog, authentication, and 15 more developer resources.

🌐 Visit website 📡 Source on GitHub

33.4/100 thin ▬ flat Agent 18/100 agent aware library Full breakdown ↓
scored 2026-09-08 · rubric v0.20.0

0 APIs

Company Gaming Web3 Artificial Intelligence Reinforcement Learning Machine-Learning gRPC SDK Developer Tools

Kin Score

Kin Score How this is scored →
scored 2026-09-08 · rubric v0.20.0

Composite quality — 33.4/100 · thin

Contract Quality 6.7 / 25

Developer Ergonomics 13.3 / 20

Access Clarity 0.0 / 20

Operational Transparency 5.5 / 13

Contract Governance 2.2 / 12

Discoverability 5.7 / 10

Agent readiness — 18/100 · agent aware

Machine-Readable Contract 18 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

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 0 / 5

Well-Known Catalog 4 / 4

Consent & Bot Identity 0 / 3

A2A Agent Card 0 / 8

Dry-Run / Simulate Mode 0 / 4

Delegated User Identity 0 / 6

Protected Resource Metadata 0 / 5

Registration Without a Human 0 / 6

Agentic Commerce Well-Known Document 0 / 5

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.

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/ai-arena: 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 →

Security Posture 3

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

Ai Arena Authentication

apiKey · 2 schemes

SECURITY

Ai Arena Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Ai Arena Vulnerability Disclosure

contact published

SECURITY

Resources

Get Started 2

Portal, sign-up, and the first successful call

DeveloperPortal

DeveloperPortal

GettingStarted

GettingStarted

Documentation 2

Reference material describing how the API behaves

Documentation

Documentation

APIReference

APIReference

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

LLMsTxt

LLMsTxt

Design & Contract 3

Pagination, idempotency, versioning, errors, and events

Lifecycle

Lifecycle

Conformance

Conformance

Conventions

Conventions

Build 4

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

Packages

SDKs

CLI

Access & Security 4

Authentication, authorization, and security posture

Authentication

Authentication

VulnerabilityDisclosure

VulnerabilityDisclosure

Security

Security

DomainSecurity

DomainSecurity

Operate 3

Status, limits, changes, and where to get help

Roadmap

Roadmap

ChangeLog

ChangeLog

Deprecation

Deprecation

Company 2

The organization behind the API

Website

Website

Blog

Blog

Other 1

Properties that don't map to a standard resource type

Protobuf

Protobuf

Source (apis.yml)

aid: ai-arena
name: AI Arena
description: 'AI Arena is a web3/AI gaming company built by ArenaX Labs, backed by Paradigm and Framework Ventures. Its flagship
  title, AI Arena, is an Ethereum/Arbitrum-native PvP fighting game where players purchase, train through imitation learning,
  and battle characters powered by real artificial intelligence, with a native $NRN (Neuron) token and an on-chain marketplace
  for AI models. Beyond the game, ArenaX Labs ships developer infrastructure for reinforcement learning: RLMesh, an open-source,
  Gymnasium-compatible framework that connects RL models to environments across process, dependency, and machine boundaries
  over a gRPC wire protocol (rlmesh-wire-v1), with Python and Rust SDKs; and SAI (competesai.com), a gamified RL research
  and competition platform with its own CLI. This profile was enriched by the API Evangelist pipeline from public sources
  — GitHub, package registries, and the RLMesh documentation.'
url: https://raw.githubusercontent.com/api-evangelist/ai-arena/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- paradigm
x-tier: stub
x-tier-reason: portfolio-lead
deliveryModel:
  model: library
  open_source: false
  commercial: false
  callable_host: false
  label: Library · distributed through package registries, no callable service
  confidence: low
  source:
  - none
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source:
  - authentication
  - security
  generated: '2026-09-03'
  method: derived
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-17'
image: https://raw.githubusercontent.com/api-evangelist/ai-arena/refs/heads/main/images/ai-arena.jpg
tags:
- Company
- Gaming
- Web3
- Artificial Intelligence
- Reinforcement Learning
- Machine-Learning
- gRPC
- SDK
- Developer Tools
tags_raw:
- Company
- Gaming
- Web3
- Artificial Intelligence
- Reinforcement Learning
- Machine Learning
- gRPC
- SDK
- Developer Tools
apis: []
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Website
  url: https://aiarena.io
- type: DeveloperPortal
  url: https://docs.rlmesh.dev
- type: Documentation
  url: https://docs.rlmesh.dev
- type: APIReference
  url: https://docs.rlmesh.dev/en/v0.1.0-rc.2/api/
- type: GettingStarted
  url: https://docs.rlmesh.dev/en/v0.1.0-rc.2/quickstart/
- type: GitHubOrganization
  url: https://github.com/ArenaX-Labs
- type: Blog
  url: https://medium.com/@aiarena
- type: Roadmap
  url: https://docs.rlmesh.dev/en/v0.1.0-rc.2/compatibility/
- type: Protobuf
  url: grpc/ai-arena-grpc.yml
- type: Packages
  url: packages/ai-arena-packages.yml
- type: SDKs
  url: packages/ai-arena-packages.yml
- type: CLI
  url: cli/ai-arena-cli.yml
- type: ChangeLog
  url: changelog/ai-arena-changelog.yml
- type: Lifecycle
  url: lifecycle/ai-arena-lifecycle.yml
- type: Deprecation
  url: https://docs.rlmesh.dev/en/v0.1.0-rc.2/compatibility/
- type: Conformance
  url: conformance/ai-arena-conformance.yml
- type: Conventions
  url: conventions/ai-arena-conventions.yml
- type: Authentication
  url: authentication/ai-arena-authentication.yml
- type: VulnerabilityDisclosure
  url: security/ai-arena-vulnerability-disclosure.yml
- type: Security
  url: https://github.com/ArenaX-Labs/rlmesh/blob/main/SECURITY.md
- type: DomainSecurity
  url: security/ai-arena-domain-security.yml
- type: LLMsTxt
  url: llms/ai-arena-llms.txt
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence

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