LunarCrush

LunarCrush is a real-time social intelligence platform for crypto, stocks, and trending topics. It aggregates billions of public posts from X (Twitter), Reddit, YouTube, TikTok, Instagram, and News across 4,000+ assets, runs them through topic classification, spam/bot filtering, sentiment scoring, and creator weighting, and turns them into proprietary metrics such as Galaxy Score, AltRank, TopicRank, CreatorRank, Social Dominance, and Sentiment. LunarCrush exposes this data through two developer surfaces: the LunarCrush API v4 (a REST API at lunarcrush.com/api4 for topics, categories, creators, posts, coins, stocks, and NFTs) and lunarcrush.ai (an AI/agent-native interface returning markdown/JSON/CSV, with a hosted Model Context Protocol server and a first-party CLI). Both use Bearer-token API-key authentication.

LunarCrush is listed with 2 APIs on the APIs.io network. Tagged areas include Company, Social Intelligence, Cryptocurrency, Stocks, and Sentiment Analysis.

LunarCrush’s developer surface includes documentation, API reference, authentication, CLI, pricing, signup flow, engineering blog, and 15 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

28.5/100 thin ▬ flat Agent 12/100 agent aware Front door AI 3/6 light Heartbeat 96/100 alive saas Full breakdown ↓
scored 2026-11-06 · rubric v0.27.0 · Show this score on your site →

2 APIs 1 MCP Servers 3 Agent Skills

Company Social Intelligence Cryptocurrency Stocks Sentiment Analysis Social Media Market Data Analytics AI Agents MCP

Kin Score

Kin Score How this is scored →
scored 2026-11-06 · rubric v0.27.0

Composite quality — 28.5/100 · thin

Contract Quality 0.0 / 21

Developer Ergonomics 9.2 / 17

Access Clarity 7.6 / 17

Operational Transparency 0.3 / 11

Contract Governance 0.5 / 10

Discoverability 6.4 / 9

Regulatory Posture 3.5 / 15

Agent readiness — 12/100 · 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 5 / 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 0 / 6

Protected Resource Metadata 0 / 5

Registration Without a Human 0 / 6

Agentic Commerce Well-Known Document 0 / 5

Pagination 5 / 5

Distinct Operations 3 / 3

MCP Tool Quality 6 / 6

Regulatory Posture applies to this provider. Its tags matched the Securities & Market Data 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/.

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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)
Stable Error Semantics +8 pts — OpenAPI $refs a shared error schema across 4xx/5xx responses (verified), else common[].type includes ErrorCatalog / ErrorCodes / DeclineCodes
A2A Agent Card +8 pts — a2a/-a2a.yml manifest, graded on conformance.grade against A2A 1.0.0
Rate-Limit Signaling +7 pts — OpenAPI responses document X-RateLimit-* / RateLimit headers (verified), else a rate_limits artifact or RateLimits link (documented)

10 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
Operational Transparency scores 2.6 — up to +12.7 composite points
Contract Governance scores 4.5 — up to +11.5 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/lunarcrush/apis.yml: open an issue on github.com/api-evangelist/lunarcrush 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 →

Standards implemented 1

Standards this provider implements or carries. De facto ones are profiled and measured by the API Commons; formal ones come from the standards directory and are linked by the provider's own tags. The evidence column says how each claim was established — not that it was made.

Model Context Protocol (MCP)

measured — observed by APIs.io (verified)

APIs 2

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

LunarCrush API v4

REST API for LunarCrush social and market intelligence. Endpoints cover trending topics, categories, creators, posts, coins, stocks, and NFTs, including summary snapshots, histo...

LunarCrush.ai

AI/agent-native interface to LunarCrush data at lunarcrush.ai. Exposes topics, categories, creators, posts, and search as clean machine-readable endpoints returning markdown by ...

MCP Servers 1

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

LunarCrush MCP

Remote MCP server at lunarcrush.ai over HTTP; 15 tools listed.

MCP SERVER

Agent Skills 3

Packaged agent skills for driving this provider's APIs from an AI assistant.

Find and profile the top creators for a topic

AGENT SKILL

Rank cryptocurrencies by social and market signal

AGENT SKILL

Get a real-time social snapshot for a topic

AGENT SKILL

Security Posture 2

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

Lunarcrush Authentication

http · 1 scheme

SECURITY

Lunarcrush Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Resources

Get Started 2

Portal, sign-up, and the first successful call

DeveloperPortal

DeveloperPortal

SignUp

SignUp

Documentation 2

Reference material describing how the API behaves

Documentation

Documentation

APIReference

APIReference

Agent Surfaces 3

MCP servers, agent skills, and machine-readable catalogs

MCPServer

MCPServer

AgentSkill

AgentSkill

LLMsTxt

LLMsTxt

Design & Contract 4

Pagination, idempotency, versioning, errors, and events

Conventions

Lifecycle

Conformance

DataModel

Build 3

SDKs, sample code, and the tooling you integrate with

CLI

CLI

Packages

Packages

GitHubOrganization

GitHubOrganization

Access & Security 2

Authentication, authorization, and security posture

Authentication

Authentication

DomainSecurity

DomainSecurity

Operate 1

Status, limits, changes, and where to get help

Support

Support

Commercial 3

Pricing, plans, and the legal terms of use

Pricing

Pricing

TermsOfService

TermsOfService

PrivacyPolicy

PrivacyPolicy

Company 2

The organization behind the API

Website

Website

Blog

Blog

Source (apis.yml)

x-enrichment:
  date: '2026-07-20'
  status: enriched
  artifacts_added: 14
  pass: local-v1
aid: lunarcrush
name: LunarCrush
description: 'LunarCrush is a real-time social intelligence platform for crypto, stocks, and trending topics. It aggregates
  billions of public posts from X (Twitter), Reddit, YouTube, TikTok, Instagram, and News across 4,000+ assets, runs them
  through topic classification, spam/bot filtering, sentiment scoring, and creator weighting, and turns them into proprietary
  metrics such as Galaxy Score, AltRank, TopicRank, CreatorRank, Social Dominance, and Sentiment. LunarCrush exposes this
  data through two developer surfaces: the LunarCrush API v4 (a REST API at lunarcrush.com/api4 for topics, categories, creators,
  posts, coins, stocks, and NFTs) and lunarcrush.ai (an AI/agent-native interface returning markdown/JSON/CSV, with a hosted
  Model Context Protocol server and a first-party CLI). Both use Bearer-token API-key authentication.'
url: https://raw.githubusercontent.com/api-evangelist/lunarcrush/refs/heads/main/apis.yml
deliveryModel:
  model: saas
  open_source: false
  commercial: true
  callable_host: false
  label: Hosted service · you call their endpoint
  confidence: medium
  source:
  - pricing
  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: '2026-11-06'
  method: derived
image: https://lunarcrush.com/apple-touch-icon.png
x-type: company
x-source: vc-portfolio
x-backed-by:
- techstars
x-tier: enriched
x-tier-reason: portfolio-lead
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-20'
tags:
- Company
- Social Intelligence
- Cryptocurrency
- Stocks
- Sentiment Analysis
- Social Media
- Market Data
- Analytics
- AI Agents
- MCP
tags_raw:
- Company
- Social Intelligence
- Cryptocurrency
- Stocks
- Sentiment Analysis
- Social Media
- Market Data
- Analytics
- AI Agents
- MCP
- Social-Media
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
apis:
- name: LunarCrush API v4
  description: REST API for LunarCrush social and market intelligence. Endpoints cover trending topics, categories, creators,
    posts, coins, stocks, and NFTs, including summary snapshots, historical time series, top posts, news, and AI "what's up"
    summaries. Authenticated with a Bearer API key.
  humanURL: https://lunarcrush.com/developers/api/endpoints
  baseURL: https://lunarcrush.com/api4
  tags:
  - Social Intelligence
  - Cryptocurrency
  - Stocks
  - Market Data
  properties:
  - type: Documentation
    url: https://lunarcrush.com/developers/api/endpoints
  - type: APIReference
    url: https://github.com/lunarcrush/api
  - type: Authentication
    url: authentication/lunarcrush-authentication.yml
- name: LunarCrush.ai
  description: AI/agent-native interface to LunarCrush data at lunarcrush.ai. Exposes topics, categories, creators, posts,
    and search as clean machine-readable endpoints returning markdown by default (JSON with ?format=json, CSV with ?format=csv),
    plus a hosted MCP server and a first-party CLI. Bearer API-key auth.
  humanURL: https://lunarcrush.ai
  baseURL: https://lunarcrush.ai
  tags:
  - AI Agents
  - MCP
  - Social Intelligence
  properties:
  - type: Documentation
    url: https://lunarcrush.ai/llms.txt
  - type: MCPServer
    url: mcp/lunarcrush-mcp.yml
  - type: CLI
    url: cli/lunarcrush-cli.yml
common:
- type: Website
  url: https://lunarcrush.com/
- type: DeveloperPortal
  url: https://lunarcrush.com/developers/api
- type: Documentation
  url: https://lunarcrush.com/developers/api/endpoints
- type: APIReference
  url: https://github.com/lunarcrush/api
- type: Authentication
  url: authentication/lunarcrush-authentication.yml
- type: MCPServer
  url: mcp/lunarcrush-mcp.yml
- type: CLI
  url: cli/lunarcrush-cli.yml
- type: Packages
  url: packages/lunarcrush-packages.yml
- type: Conventions
  url: conventions/lunarcrush-conventions.yml
- type: Lifecycle
  url: lifecycle/lunarcrush-lifecycle.yml
- type: Conformance
  url: conformance/lunarcrush-conformance.yml
- type: DataModel
  url: data-model/lunarcrush-data-model.yml
- type: AgentSkill
  url: skills/_index.yml
- type: LLMsTxt
  url: llms/lunarcrush-llms.txt
- type: DomainSecurity
  url: security/lunarcrush-domain-security.yml
- type: GitHubOrganization
  url: https://github.com/lunarcrush
- type: Pricing
  url: https://lunarcrush.com/pricing
- type: SignUp
  url: https://lunarcrush.com/signup
- type: Blog
  url: https://lunarcrush.com/blog
- type: Support
  url: https://lunarcrush.com/support
- type: TermsOfService
  url: https://lunarcrush.com/terms
- type: PrivacyPolicy
  url: https://lunarcrush.com/privacy

LunarCrush API — frequently asked questions

Does LunarCrush have an API?

Yes. APIs.io lists 2 APIs from LunarCrush, including LunarCrush API v4 and LunarCrush.ai.

How do I authenticate with the LunarCrush API?

LunarCrush uses bearer-token authentication (http · 1 scheme). The details are profiled on APIs.io as Lunarcrush Authentication.

Does LunarCrush have an MCP server?

Yes. APIs.io lists 1 MCP server for LunarCrush: Remote MCP server at lunarcrush.ai over HTTP; 15 tools listed.

Is the LunarCrush API ready for AI agents?

LunarCrush has a Kin Score of 28.5 out of 100 (thin) and an Agent Readiness score of 12.1 (agent-aware), scored by API Evangelist on 2026-11-06.

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