DataSocial

DataSocial provides a data platform offering answers about billions of TikTok creators, videos, sounds, and related metrics. The service aggregates daily historical data, enabling users to query tables and charts about creator counts, video volumes, sound usage, and follower statistics across the TikTok ecosystem. It serves analytics, research, and business intelligence use cases with a public API.

DataSocial is listed with 2 APIs on the APIs.io network. Tagged areas include Data, Analytics, TikTok, and Platform.

The DataSocial catalog on APIs.io includes 1 JSON-LD context and 1 Spectral governance ruleset.

DataSocial’s developer surface includes sandbox, documentation, and 12 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

22.1/100 emerging Agent 26/100 agent aware Full breakdown ↓
scored 2026-11-06 · rubric v0.27.0 · Show this score on your site →

2 APIs 1 MCP Servers

Data Analytics TikTok Platform

Kin Score

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

Composite quality — 22.1/100 · emerging

Contract Quality 5.5 / 21

Developer Ergonomics 2.8 / 17

Access Clarity 3.6 / 17

Operational Transparency 0.0 / 11

Contract Governance 2.2 / 10

Discoverability 4.1 / 9

Regulatory Posture 2.8 / 15

Agent readiness — 26/100 · agent aware

Machine-Readable Contract 18 / 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 7 / 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

Pagination 5 / 5

Distinct Operations 3 / 3

MCP Tool Quality 6 / 6

Regulatory Posture applies to this provider. Its tags matched the Horizontal (data, software, accessibility, platform) 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):

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)
Registration Without a Human +6 pts — a `registration_endpoint` in the served RFC 8414 / OIDC discovery document

8 more unmet checks in the Agent Readiness table above.

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

Contract Quality scores 26.1 — up to +18.5 composite points
Developer Ergonomics scores 16.7 — up to +16.7 composite points
Access Clarity scores 21.1 — up to +15.8 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/datasocial-ai/apis.yml: open an issue on github.com/api-evangelist/datasocial-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 →

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 (documented)

APIs 2

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

DataSocial MCP

Machine-readable contract exposing DataSocial's table and SQL query tools via MCP JSON-RPC.

DataSocial API

DataSocial API as documented publicly: 15 operations. Contract generated from the documentation by API Evangelist (2026-11-05); not the provider's own document.

MCP Servers 1

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

DataSocial MCP Server

Remote MCP server at api.datasocial.ai.

MCP SERVER

Semantic Vocabularies 1

JSON-LD contexts and semantic vocabularies used across these APIs.

Datasocial Ai Context

13 classes · 45 properties

JSON-LD

Spectral Rules 1

Spectral governance rulesets for linting and validating these APIs.

DataSocial API Rules

46 rules · 44 errors 1 warnings 1 info

SPECTRAL

JSON Schema 6

Standalone JSON Schema definitions for this provider's data models.

GetV1UserFollowersResponse

12 properties

JSON SCHEMA

GetV1UserFollowingResponse

13 properties

JSON SCHEMA

GetV1UserPostsResponse

10 properties

JSON SCHEMA

GetV1VideoCommentsRepliesResponse

8 properties

JSON SCHEMA

GetV1VideoCommentsResponse

14 properties

JSON SCHEMA

GetV1VideoInfoResponse

5 properties

JSON SCHEMA

Security Posture 1

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

Datasocial Ai Domain Security

TLSv1.3

SECURITY

Resources

Get Started 1

Portal, sign-up, and the first successful call

Sandbox

Sandbox

Documentation 1

Reference material describing how the API behaves

Documentation

Documentation

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

MCPServer

MCPServer

Design & Contract 5

Pagination, idempotency, versioning, errors, and events

Spectral

JSONLD

Vocabulary

DataModel

Conformance

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Commercial 2

Pricing, plans, and the legal terms of use

TermsOfService

TermsOfService

PrivacyPolicy

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: datasocial-ai
name: DataSocial
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source:
  - security
  generated: '2026-11-06'
  method: derived
image: https://datasocial.ai/og/home-v2.png
description: DataSocial provides a data platform offering answers about billions of TikTok creators, videos, sounds, and related
  metrics. The service aggregates daily historical data, enabling users to query tables and charts about creator counts, video
  volumes, sound usage, and follower statistics across the TikTok ecosystem. It serves analytics, research, and business intelligence
  use cases with a public API.
url: https://artifacts.apis.io/datasocial-ai/apis.yml
x-type: company
x-source: harvest:mcp-registry
x-tier: profiled
x-tier-reason: enrichment pass 2026-11-05 (modular-v1; was harvest)
specificationVersion: '0.20'
created: '2026-11-05'
modified: '2026-11-05'
tags:
- Data
- Analytics
- TikTok
- Platform
tags_raw:
- Data
- Analytics
- TikTok
- API
- Platform
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Spectral
  url: rules/datasocial-ai-rules.yml
- type: JSONLD
  url: json-ld/datasocial-ai-context.jsonld
- type: Vocabulary
  url: vocabulary/datasocial-ai-vocabulary.yml
- type: DataModel
  url: data-model/datasocial-ai-data-model.yml
- type: Conformance
  url: conformance/datasocial-ai-conformance.yml
- type: MCPServer
  url: mcp/datasocial-ai-mcp.yml
- type: Hosts
  url: hosts/datasocial-ai-hosts.yml
- type: Vendors
  url: vendors/datasocial-ai-vendors.yml
- type: TermsOfService
  url: https://datasocial.ai/terms
- type: Sandbox
  url: https://datasocial.ai/playground
- type: PrivacyPolicy
  url: https://datasocial.ai/privacy
- type: Documentation
  url: https://datasocial.ai/docs
- type: DomainSecurity
  url: security/datasocial-ai-domain-security.yml
- type: Website
  url: https://datasocial.ai/
apis:
- name: DataSocial MCP
  description: Machine-readable contract exposing DataSocial's table and SQL query tools via MCP JSON-RPC.
  humanURL: https://api.datasocial.ai/mcp
  baseURL: null
  contracts: null
  aid: datasocial-ai:datasocial-mcp
- aid: datasocial-ai:datasocial-ai-api
  name: DataSocial API
  description: 'DataSocial API as documented publicly: 15 operations. Contract generated from the documentation by API Evangelist
    (2026-11-05);

    not the provider''s own document.'
  humanURL: https://datasocial.ai/playground
  baseURL: https://api.datasocial.ai
  properties:
  - type: OpenAPI
    url: openapi/_ae-authored/datasocial-ai-openapi-generated.yml
    x-provenance: generated
  - type: JSONSchema
    url: json-schema/datasocial-ai-get-v1-video-comments-replies-response-schema.json
  - type: JSONSchema
    url: json-schema/datasocial-ai-get-v1-video-comments-response-schema.json
  - type: JSONSchema
    url: json-schema/datasocial-ai-get-v1-user-following-response-schema.json
  - type: JSONSchema
    url: json-schema/datasocial-ai-get-v1-user-followers-response-schema.json
  - type: JSONSchema
    url: json-schema/datasocial-ai-get-v1-video-info-response-schema.json
  - type: JSONSchema
    url: json-schema/datasocial-ai-get-v1-user-posts-response-schema.json
x-enrichment:
  date: '2026-11-05'
  status: enriched
  artifacts_added: 20
  pass: modular-v1
  engine: identity=local,contract=local,surfaces=local,docs=local,regulatory=local

DataSocial API — frequently asked questions

Does DataSocial have an API?

Yes. APIs.io lists 2 APIs from DataSocial, including DataSocial MCP and DataSocial API.

Is there an OpenAPI specification for the DataSocial API?

Yes. APIs.io indexes 1 OpenAPI specification for DataSocial, each linked for download from this page.

How do I authenticate with the DataSocial API?

DataSocial uses bearer-token authentication.

Does DataSocial have an MCP server?

Yes. APIs.io lists 1 MCP server for DataSocial: Remote MCP server at api.datasocial.ai.

Is the DataSocial API ready for AI agents?

DataSocial has a Kin Score of 22.1 out of 100 (emerging) and an Agent Readiness score of 25.9 (agent-aware), scored by API Evangelist on 2026-11-06.

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