dottxt

dottxt (styled .txt) is the company behind Outlines, the open-source structured-generation library for LLMs with 65M+ downloads. Its hosted platform API (api.dottxt.ai) is an OpenAI-compatible Chat Completions endpoint that guarantees 100% schema-compliant model output by construction using constrained decoding: pass a JSON Schema via `response_format` and the model produces exactly that shape — no retries, no validation loops, no defensive parsing. Output can be streamed as token deltas (SSE) or field-by-field as RFC 6902 JSON Patch events. dottxt also ships self-hosted, drop-in replacements for vLLM, SGLang and TensorRT-LLM inference servers, and composable libraries (dotjson for JSON Schema, dotgrammar for context-free grammars, dotlambda for function calling). Backed by EQT Ventures and Seedcamp.

dottxt publishes 6 API contracts indexed on the APIs.io network, including Models API, Batches API, Embeddings API, and 3 more. Tagged areas include Company, Artificial Intelligence, LLM, Structured Outputs, and JSON Schema.

The dottxt catalog on APIs.io includes 1 Spectral governance ruleset.

dottxt’s developer surface includes documentation, API reference, getting-started guide, signup flow, engineering blog, authentication, and 18 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

36.2/100 thin ▬ flat Agent 30/100 agent ready Front door AI 5/6 prominent Heartbeat 42/100 going silent saas Full breakdown ↓
scored 2026-11-06 · rubric v0.27.0 · Show this score on your site →

2 published contracts 1 Agent Skills

Company Artificial Intelligence LLM Structured Outputs JSON Schema Machine Learning Developer ToolsConstrained DecodingInference

Kin Score

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

Composite quality — 36.2/100 · thin

Contract Quality 7.1 / 19

Developer Ergonomics 9.2 / 15

Access Clarity 3.2 / 15

Operational Transparency 0.3 / 10

Contract Governance 1.6 / 9

Discoverability 5.5 / 8

Regulatory Posture 3.4 / 15

Create-or-Update Ergonomics 0.0 / 10

Agent readiness — 30/100 · agent ready

Machine-Readable Contract 18 / 18

Agentic Access Contract 10 / 10

Documented Reversibility 6 / 6

MCP Server 0 / 12

Machine-Readable Auth 10 / 10

Idempotency 0 / 9

Stable Error Semantics 8 / 8

Request/Response Examples 7 / 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 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 applies to this provider. This API accepts writes, so it carries 10 points of the composite. It is scored from the published contracts themselves: whether a caller can create-or-update in one call, whether the write accepts a key the caller already holds, and whether the response says which branch ran. Without that, every write needs a search-and-branch in front of it, and the first time that check is skipped a duplicate record is created. Scored against the observed mean rather than raw — a provider at the catalog average is unchanged by this facet, not penalised by it.

The six quality facets above are damped to 75 points between them, because the conditional facet above carries the other 25. That is why each facet's contribution is shown against a damped maximum: raising a quality facet moves the composite by 75% 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):

MCP Server +12 pts — deployment.mode + probe verdict on the mcp/ manifest, not the pointer; an unprobed slug falls back to authorship
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)
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
Delegated User Identity +6 pts — a served discovery document listing authorization_code in grant_types_supported (served), else an oauth2 authorizationCode flow or openIdConnect declared in an OpenAPI (documented)

6 more unmet checks in the Agent Readiness table above.

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

Access Clarity scores 21.1 — up to +15.8 composite points
Contract Quality scores 37.9 — up to +15.5 composite points
Operational Transparency scores 2.6 — up to +12.7 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/dottxt/apis.yml: open an issue on github.com/api-evangelist/dottxt 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 3

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.

JSON Schema

tagged — the provider's own APIs.json carries the standard as a tag; implementation not verified

The OpenAI Interface reaches core

declared — publishes a spec that declares them

2 core of 338 operations graded · api-commons/models

OpenAPI

measured — observed by APIs.io (published)

APIs 6

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

dottxt Models API

Models available to your API key.

dottxt Batches API

Process large volumes of requests asynchronously. Batch processing is ideal when you: - Have many requests that don't need immediate responses - Want to process data in bulk (e....

dottxt Embeddings API

Generate vector representations of text. Use embeddings for: - **Semantic search** - find content by meaning, not just keywords - **Clustering** - group similar documents togeth...

dottxt Files API

Upload and manage JSONL files for batch processing. Each line in the file should be a JSON object with: - `custom_id` - your identifier for tracking the request - `method` - HTT...

dottxt Responses API

Create model responses with enhanced capabilities. Open Responses compatible endpoint providing advanced features: - **Reasoning models** - Control computational effort with `re...

dottxt Chat Completions API

Create model responses for chat conversations. Supports: - **Multi-turn dialogue** with conversation history - **System prompts** to control model behavior - **Tool calling** fo...

Open Collections 2

Open, tool-agnostic API collections (OpenAPI-derived and Bruno).

dottxt Platform Chat API

OPEN COLLECTION

dottxt Platform Chat Models API

OPEN COLLECTION

Agent Skills 1

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

Extract structured data with dottxt

AGENT SKILL

Spectral Rules 1

Spectral governance rulesets for linting and validating these APIs.

dottxt API Rules

64 rules · 52 errors 5 warnings 7 info

SPECTRAL

OpenAPI Overlays 1

Overlays applied on top of this provider's contracts. Each card says who wrote it: a document the provider publishes, or one API Evangelist derived or generated.

Dottxt Platform Overlay

4 actions · update · dottxt-platform-openapi.yml

DERIVED

Security Posture 2

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

Dottxt Authentication

http · 1 scheme

SECURITY

Dottxt Domain Security

TLSv1.3 · HSTS · DNSSEC · DMARC

SECURITY

Agentic Access 1

Recommended x-agentic-access execution contracts for AI agents.

Dottxt Agentic Access

2 operations · 1 acting

AGENTIC

Resources

Get Started 3

Portal, sign-up, and the first successful call

DeveloperPortal

DeveloperPortal

GettingStarted

GettingStarted

SignUp

SignUp

Documentation 2

Reference material describing how the API behaves

Documentation

Documentation

APIReference

APIReference

Agent Surfaces 4

MCP servers, agent skills, and machine-readable catalogs

X-MCPServerCandidate

AgentSkill

LLMsTxt

AgenticAccess

Design & Contract 5

Pagination, idempotency, versioning, errors, and events

Conventions

ErrorCatalog

Lifecycle

Conformance

DataModel

Build 3

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

GitHubOrganization

Packages

Packages

SDKs

SDKs

Access & Security 2

Authentication, authorization, and security posture

Authentication

Authentication

DomainSecurity

DomainSecurity

Commercial 2

Pricing, plans, and the legal terms of use

TermsOfService

TermsOfService

PrivacyPolicy

PrivacyPolicy

Company 2

The organization behind the API

Website

Website

Blog

Blog

Other 1

Properties that don't map to a standard resource type

Overlay

Overlay

Source (apis.yml)

aid: dottxt
deliveryModel:
  model: saas
  open_source: false
  commercial: true
  callable_host: true
  label: Hosted service · you call their endpoint
  confidence: high
  source:
  - openapi
  - 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://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/dottxt.png
name: dottxt
description: 'dottxt (styled .txt) is the company behind Outlines, the open-source structured-generation library for LLMs
  with 65M+ downloads. Its hosted platform API (api.dottxt.ai) is an OpenAI-compatible Chat Completions endpoint that guarantees
  100% schema-compliant model output by construction using constrained decoding: pass a JSON Schema via `response_format`
  and the model produces exactly that shape — no retries, no validation loops, no defensive parsing. Output can be streamed
  as token deltas (SSE) or field-by-field as RFC 6902 JSON Patch events. dottxt also ships self-hosted, drop-in replacements
  for vLLM, SGLang and TensorRT-LLM inference servers, and composable libraries (dotjson for JSON Schema, dotgrammar for context-free
  grammars, dotlambda for function calling). Backed by EQT Ventures and Seedcamp.'
url: https://raw.githubusercontent.com/api-evangelist/dottxt/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- eqt-ventures
x-tier: enriched
x-tier-reason: portfolio-lead
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-18'
x-docs-platform: mintlify
x-docs-platform-confidence: medium
x-docs-platform-checked: 2026-09-25
x-docs-hosting: vercel
tags:
- Company
- Artificial Intelligence
- LLM
- Structured Outputs
- JSON Schema
- Machine Learning
- Developer Tools
- Constrained Decoding
- Inference
tags_raw:
- Company
- Artificial Intelligence
- LLM
- Structured Outputs
- JSON Schema
- Machine Learning
- Developer Tools
- Constrained Decoding
- JSON-Schema
- Machine-Learning
- Inference
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
apis:
- aid: dottxt:dottxt-models-api
  name: dottxt Models API
  description: Models available to your API key.
  humanURL: https://docs.dottxt.ai/api/overview
  baseURL: https://api.dottxt.ai/v1
  tags:
  - Models
  properties:
  - type: OpenAPI
    url: openapi/dottxt-models-api-openapi.yml
  - type: Documentation
    url: https://docs.dottxt.ai
  - type: APIReference
    url: https://docs.dottxt.ai/api/overview
- aid: dottxt:dottxt-batches-api
  name: dottxt Batches API
  description: 'Process large volumes of requests asynchronously.


    Batch processing is ideal when you:

    - Have many requests that don''t need immediate responses

    - Want to process data in bulk (e.g., embeddings for a document corpus)

    - Are running offline evaluations or data pipelines


    Choose your completion window: 1 hour or 24 hours. You can track progress, cancel in-flight batches, and retry failed
    requests.


    [Getting started with the Batch API →](https://docs.doubleword.ai/batches/getting-started-with-batched-api)'
  humanURL: https://docs.dottxt.ai/api/overview
  baseURL: https://api.dottxt.ai/v1
  tags:
  - batches
  properties:
  - type: OpenAPI
    url: openapi/dottxt-batches-api-openapi.yml
  - type: Documentation
    url: https://docs.dottxt.ai
  - type: APIReference
    url: https://docs.dottxt.ai/api/overview
- aid: dottxt:dottxt-embeddings-api
  name: dottxt Embeddings API
  description: 'Generate vector representations of text.


    Use embeddings for:

    - **Semantic search** - find content by meaning, not just keywords

    - **Clustering** - group similar documents together

    - **Classification** - categorize text based on similarity to examples

    - **Recommendations** - suggest related content'
  humanURL: https://docs.dottxt.ai/api/overview
  baseURL: https://api.dottxt.ai/v1
  tags:
  - embeddings
  properties:
  - type: OpenAPI
    url: openapi/dottxt-embeddings-api-openapi.yml
  - type: Documentation
    url: https://docs.dottxt.ai
  - type: APIReference
    url: https://docs.dottxt.ai/api/overview
- aid: dottxt:dottxt-files-api
  name: dottxt Files API
  description: 'Upload and manage JSONL files for batch processing.


    Each line in the file should be a JSON object with:

    - `custom_id` - your identifier for tracking the request

    - `method` - HTTP method (POST)

    - `url` - endpoint path (e.g., `/v1/chat/completions`)

    - `body` - the request payload


    [Learn more about the JSONL file format →](https://docs.doubleword.ai/batches/jsonl-files)'
  humanURL: https://docs.dottxt.ai/api/overview
  baseURL: https://api.dottxt.ai/v1
  tags:
  - files
  properties:
  - type: OpenAPI
    url: openapi/dottxt-files-api-openapi.yml
  - type: Documentation
    url: https://docs.dottxt.ai
  - type: APIReference
    url: https://docs.dottxt.ai/api/overview
- aid: dottxt:dottxt-responses-api-api
  name: dottxt Responses API
  description: 'Create model responses with enhanced capabilities.


    Open Responses compatible endpoint providing advanced features:


    - **Reasoning models** - Control computational effort with `reasoning` parameter

    - **Stateful conversations** - Maintain context across turns with `previous_response_id`

    - **Flexible input** - Use simple strings or full message arrays

    - **Text output configuration** - Structured outputs via `text` parameter

    - **Context management** - Handle overflow with `truncation` parameter


    [Open Responses API Reference →](https://www.openresponses.org/reference)'
  humanURL: https://docs.dottxt.ai/api/overview
  baseURL: https://api.dottxt.ai/v1
  tags:
  - responses-api
  properties:
  - type: OpenAPI
    url: openapi/dottxt-responses-api-api-openapi.yml
  - type: Documentation
    url: https://docs.dottxt.ai
  - type: APIReference
    url: https://docs.dottxt.ai/api/overview
- aid: dottxt:dottxt-chat-completions-api
  name: dottxt Chat Completions API
  description: 'Create model responses for chat conversations.


    Supports:

    - **Multi-turn dialogue** with conversation history

    - **System prompts** to control model behavior

    - **Tool calling** for function execution and structured outputs

    - **Streaming** for real-time token delivery

    - **Sampling parameters** like temperature, top_p, and frequency penalties'
  humanURL: https://docs.dottxt.ai/api/overview
  baseURL: https://api.dottxt.ai/v1
  tags:
  - Chat Completions
  properties:
  - type: OpenAPI
    url: openapi/dottxt-chat-completions-api-openapi.yml
  - type: Documentation
    url: https://docs.dottxt.ai
  - type: APIReference
    url: https://docs.dottxt.ai/api/overview
common:
- type: Website
  url: https://dottxt.ai/
- type: Overlay
  url: overlays/dottxt-platform-overlay.yaml
- type: DeveloperPortal
  url: https://docs.dottxt.ai
- type: Documentation
  url: https://docs.dottxt.ai
- type: APIReference
  url: https://docs.dottxt.ai/api/overview
- type: GettingStarted
  url: https://docs.dottxt.ai/quickstart
- type: SignUp
  url: https://h1xbpbfsf0w.typeform.com/to/fwQNWmS8
- type: Blog
  url: https://blog.dottxt.ai/
- type: GitHubOrganization
  url: https://github.com/dottxt-ai
- type: TermsOfService
  url: https://dottxt.ai/terms-of-service
- type: PrivacyPolicy
  url: https://dottxt.ai/privacy-policy
- type: Authentication
  url: authentication/dottxt-authentication.yml
- type: Conventions
  url: conventions/dottxt-conventions.yml
- type: ErrorCatalog
  url: errors/dottxt-problem-types.yml
- type: Lifecycle
  url: lifecycle/dottxt-lifecycle.yml
- type: Conformance
  url: conformance/dottxt-conformance.yml
- type: Packages
  url: packages/dottxt-packages.yml
- type: SDKs
  url: packages/dottxt-packages.yml
- type: X-MCPServerCandidate
  url: mcp/dottxt-mcp.yml
  note: 'Renamed from MCPServer 2026-09-03 (roadmap#247): the manifest self-describes as status: candidate — a tool list derived
    from the published API contracts, not an existing server. The scorer already read the manifest and reported mcp_server
    correctly; the MCPServer type was crediting the artifact-type surfaces with a server that does not exist.'
- type: AgentSkill
  url: skills/_index.yml
- type: LLMsTxt
  url: llms/dottxt-llms.txt
- type: DataModel
  url: data-model/dottxt-data-model.yml
- type: DomainSecurity
  url: security/dottxt-domain-security.yml
- type: AgenticAccess
  url: agentic-access/dottxt-agentic-access.yml
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence

dottxt API — frequently asked questions

Does dottxt have an API?

Yes. APIs.io lists 6 APIs from dottxt, including dottxt Models API, dottxt Batches API and dottxt Embeddings API, and 3 more.

Is there an OpenAPI specification for the dottxt API?

Yes. APIs.io indexes 6 OpenAPI specifications for dottxt, each linked for download from this page.

How do I authenticate with the dottxt API?

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

Is the dottxt API ready for AI agents?

dottxt has a Kin Score of 36.2 out of 100 (thin) and an Agent Readiness score of 30.4 (agent-ready), scored by API Evangelist on 2026-11-06.

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