dltHub

dltHub is the company behind dlt (data load tool), the open-source, Python-first data-loading library that moves data from any source to any destination with automatic schema inference, nested-JSON normalization, incremental loads, and evolving types. On top of the Apache-2.0 library, dltHub ships dlt+ (a commercial framework for productionising pipelines in teams and at scale, with Iceberg and AI workflows) and an agentic platform that deploys, monitors, and scales dlt pipelines. The developer surface is code-first: PyPI packages (dlt, dlt-plus), a rich CLI (dlt init/pipeline/schema/deploy), a first-party MCP server for agentic coding tools, and extensive documentation, tutorials, and a Slack community. dltHub is backed by Bessemer Venture Partners and operates as ScaleVector GmbH.

dltHub is profiled on the APIs.io network. Tagged areas include Company, Data, Data Engineering, ETL, and Data Pipeline.

dltHub’s developer surface includes documentation, API reference, getting-started guide, engineering blog, support, pricing, CLI, and 18 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

29.0/100 thin ▬ flat Agent 4/100 human only Front door AI 6/6 dominant Heartbeat 78/100 alive saas Full breakdown ↓
scored 2026-11-13 · rubric v0.28.0 · Show this score on your site →

0 APIs 1 MCP Servers

Company Data Data Engineering ETL Data Pipeline Python Open Source Data Integration AI Agents MCP

Kin Score

Kin Score How this is scored →
scored 2026-11-13 · rubric v0.28.0

Composite quality — 29.0/100 · thin

Contract Quality 0.0 / 21

Developer Ergonomics 10.1 / 17

Access Clarity 8.7 / 17

Operational Transparency 2.1 / 11

Contract Governance 0.0 / 10

Discoverability 4.7 / 9

Regulatory Posture 1.2 / 15

Agent readiness — 4/100 · human only

Machine-Readable Contract 0 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 12 / 12

Machine-Readable Auth 0 / 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 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):

Machine-Readable Contract +18 pts — api_specs includes an OpenAPI document Ask about this →
Agentic Access Contract +10 pts — agentic_access artifact present (x-agentic-access), graded by author Ask about this →
Machine-Readable Auth +10 pts — a served openid-configuration/oauth-authorization-server carrying `issuer` (served), else the securitySchemes class in the provider OpenAPIs — bound (mutualTLS, DPoP, Signature) > negotiable (oauth2 authorizationCode/clientCredentials, openIdConnect) > bearer (http bearer, apiKey) Ask about this →
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) Ask about this →
Stable Error Semantics +8 pts — OpenAPI $refs a shared error schema across 4xx/5xx responses (verified), else common[].type includes ErrorCatalog / ErrorCodes / DeclineCodes Ask about this →
A2A Agent Card +8 pts — a2a/-a2a.yml manifest, graded on conformance.grade against A2A 1.0.0 Ask about this →

12 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 Ask about this →
Contract Governance scores 0.0 — up to +12.0 composite points Ask about this →
Operational Transparency scores 19.0 — up to +10.5 composite points Ask about this →

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.

Not sure how this applies to your stack? Ask about any one item. Kin Lane reads every question, looks at your profile and your situation, and replies with what a fix would take — scoped to that one area, priced up front, yours whether you ship it or not. Ask a question →

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/dlthub/apis.yml: open an issue on github.com/api-evangelist/dlthub 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 →

Markets this provider is in provisional

The Kin Score Market layer reads a provider inside its market: its position, and how deep its integrations go. Depth is only comparable within a position. Provisional and unweighted: not part of the Kin Score or agent readiness.

Market	Position	Depth	Registered MCP server	Declares compatibility
Data Integration (ELT connectors and data governance)	builds-on	26.8 (thin)	-	1

Registered MCP server and declares compatibility are report only — not weighted. Undeclared means we found nothing we can read, so there is no number: we never infer integrations.

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)

MCP Servers 1

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

dltHub MCP Server

Local (stdio) MCP server.

MCP SERVER

Terms of Service 1

What its API terms permit and prohibit, quoted from its own page.

dltHub

11 quoted statements, read from dltHub's own page on 2026-11-09.

TERMS

Privacy & Data 1

Its role, the data it processes, retention and transfers, quoted from its own privacy page.

dltHub

19 quoted statements, read from dltHub's own page on 2026-11-09.

PRIVACY

Eligibility 1

Who may sign up and where, quoted from its own terms.

dltHub

3 quoted statements, read from dltHub's own page on 2026-11-09.

ELIGIBILITY

AI Preferences 1

Its stance on AI training, inference and agents, quoted from its own pages.

dltHub

1 quoted statement, read from dltHub's own page on 2026-11-09.

AI PREFS

Data License 1

How its data and outputs may be reused, quoted from its own terms.

dltHub

2 quoted statements, read from dltHub's own page on 2026-11-09.

LICENSE

Security Posture 1

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

dltHub Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Resources

Get Started 3

Portal, sign-up, and the first successful call

DeveloperPortal

DeveloperPortal

GettingStarted

GettingStarted

Login

Documentation 3

Reference material describing how the API behaves

Documentation

Documentation

APIReference

APIReference

AIPreferences

AIPreferences

Agent Surfaces 2

MCP servers, agent skills, and machine-readable catalogs

MCPServer

MCPServer

LLMsTxt

LLMsTxt

Build 4

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

Packages

SDKs

CLI

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Operate 2

Status, limits, changes, and where to get help

Support

Support

ChangeLog

ChangeLog

Commercial 5

Pricing, plans, and the legal terms of use

Pricing

TermsOfService

PrivacyPolicy

UsageTerms

DataLicense

Company 3

The organization behind the API

Website

Website

Blog

Blog

BlogRSS

BlogRSS

Other 2

Properties that don't map to a standard resource type

DataProcessing

DataProcessing

Eligibility

Eligibility

Source (apis.yml)

aid: dlthub
name: dltHub
description: 'dltHub is the company behind dlt (data load tool), the open-source, Python-first data-loading library that moves
  data from any source to any destination with automatic schema inference, nested-JSON normalization, incremental loads, and
  evolving types. On top of the Apache-2.0 library, dltHub ships dlt+ (a commercial framework for productionising pipelines
  in teams and at scale, with Iceberg and AI workflows) and an agentic platform that deploys, monitors, and scales dlt pipelines.
  The developer surface is code-first: PyPI packages (dlt, dlt-plus), a rich CLI (dlt init/pipeline/schema/deploy), a first-party
  MCP server for agentic coding tools, and extensive documentation, tutorials, and a Slack community. dltHub is backed by
  Bessemer Venture Partners and operates as ScaleVector GmbH.'
url: https://raw.githubusercontent.com/api-evangelist/dlthub/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:
  - security
  generated: '2026-11-13'
  method: derived
image: https://dlthub.com/api/og?title=dltHub&kind=default
x-type: company
x-source: vc-portfolio
x-backed-by:
- bessemer-venture-partners
x-tier: stub
x-tier-reason: portfolio-lead
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-18'
tags:
- Company
- Data
- Data Engineering
- ETL
- Data Pipeline
- Python
- Open Source
- Data Integration
- AI Agents
- MCP
tags_raw:
- Company
- Data
- Data Engineering
- ETL
- Data Pipelines
- Python
- Open Source
- Data Integration
- Agentic
- MCP
- Open-Source
apis: []
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Website
  url: https://dlthub.com/
- type: DeveloperPortal
  url: https://dlthub.com/docs
- type: Documentation
  url: https://dlthub.com/docs/intro
- type: APIReference
  url: https://dlthub.com/docs/reference
- type: GettingStarted
  url: https://dlthub.com/docs/tutorial/rest-api
- type: Blog
  url: https://dlthub.com/blog
- type: BlogRSS
  url: https://dlthub.com/blog/rss.xml
- type: Support
  url: https://dlthub.com/community
- type: GitHubOrganization
  url: https://github.com/dlt-hub
- type: Pricing
  url: https://dlthub.com/pricing
- type: Login
  url: https://app.dlthub.com/login
- type: TermsOfService
  url: https://dlthub.com/terms
- type: PrivacyPolicy
  url: https://dlthub.com/privacy-policy
- type: Packages
  url: packages/dlthub-packages.yml
- type: SDKs
  url: packages/dlthub-packages.yml
- type: CLI
  url: cli/dlthub-cli.yml
- type: MCPServer
  url: mcp/dlthub-mcp.yml
- type: LLMsTxt
  url: llms/dlthub-llms.txt
- type: ChangeLog
  url: changelog/dlthub-changelog.yml
- type: DomainSecurity
  url: security/dlthub-domain-security.yml
- type: UsageTerms
  url: terms/dlthub-terms-of-service.yml
- type: DataProcessing
  url: privacy/dlthub-privacy-policy.yml
- type: Eligibility
  url: eligibility/dlthub-eligibility.yml
- type: AIPreferences
  url: ai-preferences/dlthub-ai-preferences.yml
- type: DataLicense
  url: data-license/dlthub-data-license.yml
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence

dltHub API — frequently asked questions

Does dltHub have an MCP server?

Yes. APIs.io lists 1 MCP server for dltHub: Local (stdio) MCP server.

Is the dltHub API ready for AI agents?

dltHub has a Kin Score of 29.0 out of 100 (thin) and an Agent Readiness score of 3.5 (human-only), scored by API Evangelist on 2026-11-13.

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.

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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.

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