LMQL

LMQL provides a powerful query language for large language models, enabling developers to write expressive, constraint‑driven prompts that combine probabilistic reasoning with deterministic logic. The platform offers an open‑source SDK, cloud‑hosted execution, and integrations with major LLM providers, allowing seamless incorporation of advanced prompting techniques into applications ranging from chatbots to data analysis pipelines. LMQL’s documentation includes tutorials, API references, and example notebooks, helping users adopt the technology quickly and efficiently.

LMQL is profiled on the APIs.io network. Tagged areas include Company, Artificial Intelligence, Query Language, LLM, and Open Source.

LMQL’s developer surface includes sandbox, documentation, engineering blog, getting-started guide, and 6 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

10.6/100 minimal Agent 3/100 human only Full breakdown ↓
scored 2026-10-23 · rubric v0.25.0 · Show this score on your site →

0 APIs

Company Artificial Intelligence Query Language LLM Open Source

Kin Score

Kin Score How this is scored →
scored 2026-10-23 · rubric v0.25.0

Composite quality — 10.6/100 · minimal

Contract Quality 0.0 / 21

Developer Ergonomics 6.5 / 17

Access Clarity 0.0 / 17

Operational Transparency 0.0 / 11

Contract Governance 0.0 / 10

Discoverability 3.8 / 9

Regulatory Posture 0.8 / 15

Agent readiness — 3/100 · 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

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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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/lmql: 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 1

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

Lmql Domain Security

TLSv1.3

SECURITY

Resources

Get Started 2

Portal, sign-up, and the first successful call

Sandbox

Sandbox

GettingStarted

GettingStarted

Documentation 1

Reference material describing how the API behaves

Documentation

Documentation

Build 2

SDKs, sample code, and the tooling you integrate with

SDKs

SDKs

Packages

Packages

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Company 2

The organization behind the API

Blog

Blog

Website

Website

Other 2

Properties that don't map to a standard resource type

Hosts

Hosts

Vendors

Vendors

Source (apis.yml)

aid: lmql
name: LMQL
description: LMQL provides a powerful query language for large language models, enabling developers to write expressive, constraint‑driven
  prompts that combine probabilistic reasoning with deterministic logic. The platform offers an open‑source SDK, cloud‑hosted
  execution, and integrations with major LLM providers, allowing seamless incorporation of advanced prompting techniques into
  applications ranging from chatbots to data analysis pipelines. LMQL’s documentation includes tutorials, API references,
  and example notebooks, helping users adopt the technology quickly and efficiently.
url: https://raw.githubusercontent.com/api-evangelist/lmql/refs/heads/main/apis.yml
x-type: company
x-source: harvest:g2-catalog
x-tier: profiled
x-tier-reason: enrichment pass 2026-10-20 (modular-v1; was harvest)
specificationVersion: '0.20'
created: '2026-10-20'
modified: '2026-10-20'
tags:
- Company
- Artificial Intelligence
- Query Language
- LLM
- Open Source
tags_raw:
- Company
- AI
- QueryLanguage
- LLM
- OpenSource
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Hosts
  url: hosts/lmql-hosts.yml
- type: Vendors
  url: vendors/lmql-vendors.yml
- type: SDKs
  url: packages/lmql-packages.yml
- type: Packages
  url: packages/lmql-packages.yml
- type: Sandbox
  url: https://lmql.ai/playground
- type: Documentation
  url: https://lmql.ai/docs/
- type: Blog
  url: https://lmql.ai/blog/
- type: GettingStarted
  url: https://lmql.ai/docs/index.html
- type: DomainSecurity
  url: security/lmql-domain-security.yml
- type: Website
  url: https://lmql.ai/
apis: []
x-coverage:
  state: unreadable
  reason: js-rendered-docs
  detail: Documentation is rendered via JavaScript and no machine‑readable OpenAPI spec was found.
  evidence:
  - url: https://lmql.ai/docs/
    status: 200
  checked: '2026-10-20'
x-enrichment:
  date: '2026-10-20'
  status: enriched
  artifacts_added: 8
  pass: modular-v1
  engine: identity=local,contract=local,surfaces=local,docs=local,regulatory=local

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