LM Studio

LM Studio is a desktop application for discovering, downloading, and running large language models (Llama, DeepSeek, Phi, Qwen, gpt-oss, and others) locally on macOS, Windows, and Linux. It runs GGUF and MLX models via llama.cpp and Apple's MLX engine, and ships a local HTTP server that developers can drive from their own apps: a native LM Studio REST API (beta) under /api/v1 with generation stats, model load/unload/download and MCP-via-API, an OpenAI-compatible surface under /v1 (chat/completions, completions, embeddings, models, responses), and an Anthropic-compatible /v1/messages endpoint. It is complemented by Python (lmstudio) and TypeScript (@lmstudio/sdk) SDKs, the MIT-licensed lms command-line tool, headless/daemon operation, LM Link cross-device routing, and MCP host support. Backed by Matrix Partners.

LM Studio publishes 4 API contracts indexed on the APIs.io network, including Anthropic Compatibility API, Chat API, Models API, and 1 more. Tagged areas include Company, Artificial Intelligence, Local LLM, Machine Learning, and Inference.

The LM Studio catalog on APIs.io includes 1 Spectral governance ruleset.

LM Studio’s developer surface includes documentation, API reference, getting-started guide, engineering blog, support, CLI, authentication, and 20 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

30.1/100 thin ▬ flat Agent 18/100 agent aware Front door AI 3/6 light Heartbeat 94/100 alive saas Full breakdown ↓
scored 2026-11-06 · rubric v0.27.0 · Show this score on your site →

1 published contract 2 Agent Skills

Company Artificial IntelligenceLocal LLMMachine Learning Inference Developer Tools LLM MCP SDK Desktop Application

Kin Score

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

Composite quality — 30.1/100 · thin

Contract Quality 2.2 / 19

Developer Ergonomics 9.6 / 15

Access Clarity 3.2 / 15

Operational Transparency 0.3 / 10

Contract Governance 1.6 / 9

Discoverability 4.8 / 8

Regulatory Posture 4.2 / 15

Create-or-Update Ergonomics 0.0 / 10

Agent readiness — 18/100 · agent aware

Machine-Readable Contract 18 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 0 / 12

Machine-Readable Auth 10 / 10

Idempotency 0 / 9

Stable Error Semantics 8 / 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 0 / 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
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)
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)
Request/Response Examples +7 pts — share of operations carrying request/response examples; else an Examples / Code Samples link

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 11.9 — up to +22.0 composite points
Access Clarity scores 21.1 — up to +15.8 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/lm-studio/apis.yml: open an issue on github.com/api-evangelist/lm-studio 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
Obsidian Community Plugins (third-party APIs the Obsidian plugin ecosystem integrates)	distribution	21.7	-	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 2

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)

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

OpenAPI

measured — observed by APIs.io (published)

APIs 4

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

LM Studio Anthropic Compatibility API

Anthropic-compatible messages endpoint.

LM Studio Chat API

Native LM Studio chat inference with generation stats.

LM Studio Models API

List, load, unload, and download local models.

LM Studio OpenAI Compatibility API

OpenAI-compatible endpoints for reuse of existing OpenAI clients.

Open Collections 4

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

LM Studio Local Server Anthropic Compatibility API

OPEN COLLECTION

LM Studio Local Server Anthropic Compatibility Chat API

OPEN COLLECTION

LM Studio Local Server Anthropic Compatibility Models API

OPEN COLLECTION

LM Studio Local Server Anthropic Compatibility OpenAI Compatibility API

OPEN COLLECTION

Agent Skills 2

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

Load a model and run a chat

AGENT SKILL

Use LM Studio as an OpenAI drop-in

AGENT SKILL

Spectral Rules 1

Spectral governance rulesets for linting and validating these APIs.

LM Studio API Rules

47 rules · 45 errors 1 warnings 1 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.

Lm Studio Server Overlay

3 actions · update · lm-studio-server-openapi.yml

DERIVED

Security Posture 3

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

Lm Studio Authentication

http · 1 scheme

SECURITY

Lm Studio Domain Security

TLSv1.3 · DNSSEC · DMARC

SECURITY

Lm Studio Vulnerability Disclosure

no policy recorded

SECURITY

Resources

Get Started 2

Portal, sign-up, and the first successful call

DeveloperPortal

DeveloperPortal

GettingStarted

GettingStarted

Documentation 2

Reference material describing how the API behaves

Documentation

Documentation

APIReference

APIReference

Agent Surfaces 3

MCP servers, agent skills, and machine-readable catalogs

X-MCPServerCandidate

X-MCPServerCandidate

LLMsTxt

LLMsTxt

AgentSkill

AgentSkill

Design & Contract 5

Pagination, idempotency, versioning, errors, and events

Conventions

ErrorCatalog

Lifecycle

Conformance

DataModel

Build 4

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

Packages

SDKs

CLI

Access & Security 4

Authentication, authorization, and security posture

Authentication

Authentication

VulnerabilityDisclosure

VulnerabilityDisclosure

Security

Security

DomainSecurity

DomainSecurity

Operate 1

Status, limits, changes, and where to get help

Support

Support

Commercial 2

Pricing, plans, and the legal terms of use

TermsOfService

TermsOfService

PrivacyPolicy

PrivacyPolicy

Company 3

The organization behind the API

BlogRSS

BlogRSS

Website

Website

Blog

Blog

Other 1

Properties that don't map to a standard resource type

Overlay

Overlay

Source (apis.yml)

aid: lm-studio
name: LM Studio
description: 'LM Studio is a desktop application for discovering, downloading, and running large language models (Llama, DeepSeek,
  Phi, Qwen, gpt-oss, and others) locally on macOS, Windows, and Linux. It runs GGUF and MLX models via llama.cpp and Apple''s
  MLX engine, and ships a local HTTP server that developers can drive from their own apps: a native LM Studio REST API (beta)
  under /api/v1 with generation stats, model load/unload/download and MCP-via-API, an OpenAI-compatible surface under /v1
  (chat/completions, completions, embeddings, models, responses), and an Anthropic-compatible /v1/messages endpoint. It is
  complemented by Python (lmstudio) and TypeScript (@lmstudio/sdk) SDKs, the MIT-licensed lms command-line tool, headless/daemon
  operation, LM Link cross-device routing, and MCP host support. Backed by Matrix Partners.'
url: https://raw.githubusercontent.com/api-evangelist/lm-studio/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- matrix-partners
deliveryModel:
  model: saas
  open_source: false
  commercial: true
  callable_host: false
  label: Hosted service · you call their endpoint
  confidence: medium
  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
  try_now_blocked_by: loopback
  source:
  - authentication
  - security
  generated: '2026-11-06'
  method: derived
image: https://files.lmstudio.ai/bionic/lm-studio-bionic-og.jpg
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-10-06'
tags:
- Company
- Artificial Intelligence
- Local LLM
- Machine Learning
- Inference
- Developer Tools
- LLM
- MCP
- SDK
- Desktop Application
tags_raw:
- Company
- Ai
- Local LLM
- Machine Learning
- Inference
- Developer Tools
- LLM
- MCP
- SDK
- Desktop Application
- Machine-Learning
apis:
- aid: lm-studio:lm-studio-anthropic-compatibility-api
  name: LM Studio Anthropic Compatibility API
  description: Anthropic-compatible messages endpoint.
  humanURL: https://lmstudio.ai/docs/app/api/endpoints/rest
  baseURL: http://localhost:1234
  tags:
  - Anthropic Compatibility
  properties:
  - type: OpenAPI
    url: openapi/lm-studio-anthropic-compatibility-api-openapi.yml
  - type: Authentication
    url: authentication/lm-studio-authentication.yml
  - type: Conventions
    url: conventions/lm-studio-conventions.yml
  - type: ErrorCatalog
    url: errors/lm-studio-problem-types.yml
  - type: DataModel
    url: data-model/lm-studio-data-model.yml
  - type: Conformance
    url: conformance/lm-studio-conformance.yml
  - type: Lifecycle
    url: lifecycle/lm-studio-lifecycle.yml
- aid: lm-studio:lm-studio-chat-api
  name: LM Studio Chat API
  description: Native LM Studio chat inference with generation stats.
  humanURL: https://lmstudio.ai/docs/app/api/endpoints/rest
  baseURL: http://localhost:1234
  tags:
  - Chat
  properties:
  - type: OpenAPI
    url: openapi/lm-studio-chat-api-openapi.yml
  - type: Authentication
    url: authentication/lm-studio-authentication.yml
  - type: Conventions
    url: conventions/lm-studio-conventions.yml
  - type: ErrorCatalog
    url: errors/lm-studio-problem-types.yml
  - type: DataModel
    url: data-model/lm-studio-data-model.yml
  - type: Conformance
    url: conformance/lm-studio-conformance.yml
  - type: Lifecycle
    url: lifecycle/lm-studio-lifecycle.yml
- aid: lm-studio:lm-studio-models-api
  name: LM Studio Models API
  description: List, load, unload, and download local models.
  humanURL: https://lmstudio.ai/docs/app/api/endpoints/rest
  baseURL: http://localhost:1234
  tags:
  - Models
  properties:
  - type: OpenAPI
    url: openapi/lm-studio-models-api-openapi.yml
  - type: Authentication
    url: authentication/lm-studio-authentication.yml
  - type: Conventions
    url: conventions/lm-studio-conventions.yml
  - type: ErrorCatalog
    url: errors/lm-studio-problem-types.yml
  - type: DataModel
    url: data-model/lm-studio-data-model.yml
  - type: Conformance
    url: conformance/lm-studio-conformance.yml
  - type: Lifecycle
    url: lifecycle/lm-studio-lifecycle.yml
- aid: lm-studio:lm-studio-openai-compatibility-api
  name: LM Studio OpenAI Compatibility API
  description: OpenAI-compatible endpoints for reuse of existing OpenAI clients.
  humanURL: https://lmstudio.ai/docs/app/api/endpoints/rest
  baseURL: http://localhost:1234
  tags:
  - OpenAI Compatibility
  properties:
  - type: OpenAPI
    url: openapi/lm-studio-openai-compatibility-api-openapi.yml
  - type: Authentication
    url: authentication/lm-studio-authentication.yml
  - type: Conventions
    url: conventions/lm-studio-conventions.yml
  - type: ErrorCatalog
    url: errors/lm-studio-problem-types.yml
  - type: DataModel
    url: data-model/lm-studio-data-model.yml
  - type: Conformance
    url: conformance/lm-studio-conformance.yml
  - type: Lifecycle
    url: lifecycle/lm-studio-lifecycle.yml
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- url: https://lmstudio.ai/rss.xml
  type: BlogRSS
- type: Overlay
  url: overlays/lm-studio-server-overlay.yaml
- type: Website
  url: https://lmstudio.ai
- type: DeveloperPortal
  url: https://lmstudio.ai/docs
- type: Documentation
  url: https://lmstudio.ai/docs
- type: APIReference
  url: https://lmstudio.ai/docs/app/api/endpoints/rest
- type: GettingStarted
  url: https://lmstudio.ai/docs/app
- type: Blog
  url: https://lmstudio.ai/blog
- type: GitHubOrganization
  url: https://github.com/lmstudio-ai
- type: Support
  url: https://github.com/lmstudio-ai/lmstudio-bug-tracker
- type: TermsOfService
  url: https://lmstudio.ai/terms
- type: PrivacyPolicy
  url: https://lmstudio.ai/privacy
- type: Packages
  url: packages/lm-studio-packages.yml
- type: SDKs
  url: packages/lm-studio-packages.yml
- type: CLI
  url: cli/lm-studio-cli.yml
- type: X-MCPServerCandidate
  url: mcp/lm-studio-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: Authentication
  url: authentication/lm-studio-authentication.yml
- type: Conventions
  url: conventions/lm-studio-conventions.yml
- type: ErrorCatalog
  url: errors/lm-studio-problem-types.yml
- type: Lifecycle
  url: lifecycle/lm-studio-lifecycle.yml
- type: Conformance
  url: conformance/lm-studio-conformance.yml
- type: DataModel
  url: data-model/lm-studio-data-model.yml
- type: LLMsTxt
  url: llms/lm-studio-llms.txt
- type: AgentSkill
  url: skills/_index.yml
- type: VulnerabilityDisclosure
  url: security/lm-studio-vulnerability-disclosure.yml
- type: Security
  url: https://lmstudio.ai/vulnerability-disclosure
- type: DomainSecurity
  url: security/lm-studio-domain-security.yml
x-enrichment:
  date: '2026-07-20'
  status: enriched
  artifacts_added: 18
  pass: local-v1

LM Studio API — frequently asked questions

Does LM Studio have an API?

Yes. APIs.io lists 4 APIs from LM Studio, including LM Studio Anthropic Compatibility API, LM Studio Chat API and LM Studio Models API, and 1 more.

Is there an OpenAPI specification for the LM Studio API?

Yes. APIs.io indexes 4 OpenAPI specifications for LM Studio, each linked for download from this page.

How do I authenticate with the LM Studio API?

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

Is the LM Studio API ready for AI agents?

LM Studio has a Kin Score of 30.1 out of 100 (thin) and an Agent Readiness score of 18.2 (agent-aware), scored by API Evangelist on 2026-11-06.

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