Tabby

Tabby is an open-source, self-hosted AI coding assistant - a privacy-first alternative to GitHub Copilot from TabbyML (Apache-2.0). You run the Tabby server yourself (Docker, a consumer-grade GPU, or your own cloud); there is no shared multi-tenant API and no external calls to third parties. The server exposes an OpenAPI-documented REST surface (Swagger UI at /swagger-ui, spec at /api-docs/openapi.json) for code completion, OpenAI-compatible chat completions, an Answer Engine backed by a doc-ingestion knowledge base, health, model registry, and telemetry events. Because it is self-hosted, the base URL is your own instance (default http://localhost:8080). TabbyML also offers hosted Team and Enterprise plans.

Tabby publishes 6 API contracts indexed on the APIs.io network, including Completions API, Events API, Health API, and 3 more. Tagged areas include AI Coding Assistant, Code Completion, Open Source, Developer Tools, and LLM.

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

Tabby’s developer surface includes pricing, authentication, documentation, engineering blog, and 9 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

32.4/100 thin ▬ flat Agent 20/100 agent aware Front door AI 6/6 dominant Heartbeat 38/100 alive saas Full breakdown ↓
scored 2026-11-06 · rubric v0.27.0 · Show this score on your site →

AccessFreemiumSelf serve

1 published contract

AI Coding Assistant Code Completion Open Source Developer Tools LLM Artificial Intelligence Self-Hosted Code GenerationCopilot Alternative

What this lets a business do 1

Business capabilities this provider's published APIs can perform, derived from its own contracts. Browse all capabilities →

Product Telemetry & Experimentation Management

BC-4280

Events

POST /v1/events

Kin Score

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

Composite quality — 32.4/100 · thin

Contract Quality 8.4 / 19

Developer Ergonomics 4.8 / 15

Access Clarity 5.5 / 15

Operational Transparency 1.0 / 10

Contract Governance 1.2 / 9

Discoverability 4.3 / 8

Regulatory Posture 1.6 / 15

Create-or-Update Ergonomics 0.0 / 10

Agent readiness — 20/100 · agent aware

Machine-Readable Contract 18 / 18

Agentic Access Contract 10 / 10

Documented Reversibility 0 / 6

MCP Server 0 / 12

Machine-Readable Auth 10 / 10

Idempotency 0 / 9

Stable Error Semantics 0 / 8

Request/Response Examples 0 / 7

Rate-Limit Signaling 7 / 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 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)
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
Request/Response Examples +7 pts — share of operations carrying request/response examples; else an Examples / Code Samples link
Registration Without a Human +6 pts — a `registration_endpoint` in the served RFC 8414 / OIDC discovery document

9 more unmet checks in the Agent Readiness table above.

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

Contract Quality scores 44.9 — up to +13.8 composite points
Developer Ergonomics scores 32.1 — up to +13.6 composite points
Access Clarity scores 36.8 — up to +12.6 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/tabby-ml/apis.yml: open an issue on github.com/api-evangelist/tabby-ml 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
IDE Extension Marketplaces (JetBrains, VS Code, Open VSX, Docker Verified Publishers, PyPI orgs)	builds-on	34.5 (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 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.

The OpenAI Interface reaches extended

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.

Tabby Completions API

Code completion endpoint powering Tabby's IDE plugins.

Tabby Events API

Client telemetry event logging.

Tabby Health API

Server health and settings.

Tabby Ingestion API

Doc ingestion into the Answer Engine knowledge base.

Tabby Models API

Model registry configured on the server.

Tabby Chat Completions API

OpenAI-compatible chat completions and inline chat / Answer Engine.

Open Collections 7

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

Tabby Server Chat API

OPEN COLLECTION

Tabby Server Chat Completions API

OPEN COLLECTION

Tabby Server Chat Events API

OPEN COLLECTION

Tabby Server Chat Health API

OPEN COLLECTION

Tabby Server Chat Ingestion API

OPEN COLLECTION

Tabby Server Chat Models API

OPEN COLLECTION

Tabby Server API

OPEN COLLECTION

Scroll for all 7

Tabby API pricing

Prices published by Tabby, read 2026-10-07 from www.tabbyml.com/pricing. A free plan or tier is listed.

Plan	Price
Community	Free Includes: Up to 5 users, Local deployment, Code Completion, Answer Engine, In-line chat & Context Provider
Team	$19/mo per seat Includes: Up to 50 users, Flexible deployment
Enterprise	Custom Includes: Unlimited users, Customised deployment, Enhanced security and group management
Basic Plan (annual billing)	$180/yr Includes: Real-time code analysis, Integrated code documentation, Collaboration tools
Business Plan (annual billing)	$280/yr Includes: Advanced code suggestions, Priority email support, plus Basic features
Enterprise Plan (annual billing)	$480/yr Includes: Priority email support, Advanced code suggestions, plus all features
Tabby Cloud Usage-Based (Pochi)	$20 in free monthly credits Includes: Bills based on token cost of LLMs; Tab Completion always free

Plan details, limits and sources →

Rate limits

Completion / Chat Throughput: hardware-bound requests
API Request Rate: not published requests
Doc Ingestion: not published documents

Compiled by API Evangelist, not yet checked against Tabby's documentation. All 4 limits →

Pricing Plans 1

Published pricing tiers and plan structures.

Tabby Ml Plans Pricing

7 plans

PLANS

Rate Limits 1

Documented rate limits and quota policies.

Tabby Ml Rate Limits

4 limits

RATE LIMITS

Service Levels 1

Uptime the provider promises or reports, as SLA4OAI. Read from its own pages; APIs.io runs no monitors.

Tabby

SLA

FinOps 1

Cost, billing, and metering signals for API financial operations.

Tabby Ml Finops

FINOPS

Spectral Rules 1

Spectral governance rulesets for linting and validating these APIs.

Tabby API Rules

57 rules · 55 errors 1 warnings 1 info

SPECTRAL

Security Posture 2

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

Tabby Ml Authentication

http · 1 scheme

SECURITY

Tabby Ml Domain Security

HSTS

SECURITY

Agentic Access 1

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

Tabby Ml Agentic Access

8 operations · 5 acting

AGENTIC

Resources

Documentation 1

Reference material describing how the API behaves

Documentation

Documentation

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

AgenticAccess

AgenticAccess

Build 1

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

GitHubOrganization

Access & Security 2

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Authentication

Authentication

Operate 1

Status, limits, changes, and where to get help

RateLimits

RateLimits

Commercial 3

Pricing, plans, and the legal terms of use

Pricing

Pricing

Plans

Plans

FinOps

FinOps

Company 3

The organization behind the API

LinkedIn

Website

Website

Blog

Blog

Other 1

Properties that don't map to a standard resource type

CapabilityMap

CapabilityMap

Source (apis.yml)

aid: tabby-ml
url: https://raw.githubusercontent.com/api-evangelist/tabby-ml/refs/heads/main/apis.yml
name: Tabby
kind: company
description: Tabby is an open-source, self-hosted AI coding assistant - a privacy-first alternative to GitHub Copilot from
  TabbyML (Apache-2.0). You run the Tabby server yourself (Docker, a consumer-grade GPU, or your own cloud); there is no shared
  multi-tenant API and no external calls to third parties. The server exposes an OpenAPI-documented REST surface (Swagger
  UI at /swagger-ui, spec at /api-docs/openapi.json) for code completion, OpenAI-compatible chat completions, an Answer Engine
  backed by a doc-ingestion knowledge base, health, model registry, and telemetry events. Because it is self-hosted, the base
  URL is your own instance (default http://localhost:8080). TabbyML also offers hosted Team and Enterprise plans.
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: freemium
  onboarding: self-serve
  trial: false
  try_now: false
  public: false
  gated: none
  gated_source:
  - onboarding
  label: Freemium · Self-serve signup
  confidence: medium
  try_now_blocked_by: loopback
  source:
  - plans
  - authentication
  - security
  generated: '2026-11-06'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/tabby-ml.png
tags:
- AI Coding Assistant
- Code Completion
- Open Source
- Developer Tools
- LLM
- Artificial Intelligence
- Self-Hosted
- Code Generation
- Copilot Alternative
tags_raw:
- AI Coding Assistant
- Code Completion
- Open Source
- Developer Tools
- LLM
- AI
- Self-Hosted
- Code Generation
- Copilot Alternative
- Open-Source
created: '2026-07-11'
modified: '2026-07-11'
specificationVersion: '0.23'
apis:
- aid: tabby-ml:tabby-ml-completions-api
  name: Tabby Completions API
  description: Code completion endpoint powering Tabby's IDE plugins.
  humanURL: https://tabby.tabbyml.com/docs/api/
  baseURL: http://localhost:8080
  tags:
  - Completions
  properties:
  - type: OpenAPI
    url: openapi/tabby-ml-completions-api-openapi.yml
  - type: Documentation
    url: https://tabby.tabbyml.com/docs/welcome/
  - type: APIReference
    url: https://tabby.tabbyml.com/api/
  - type: OpenCollection
    url: collections/tabby-ml.opencollection.json
  - type: PostmanCollection
    url: collections/tabby-ml.postman_collection.json
  - type: Documentation
    url: https://tabby.tabbyml.com/docs/administration/answer-engine/
  - type: Documentation
    url: https://www.tabbyml.com/blog/doc-ingestion-api
  - type: Documentation
    url: https://tabby.tabbyml.com/docs/references/models-http-api/openai/
- aid: tabby-ml:tabby-ml-events-api
  name: Tabby Events API
  description: Client telemetry event logging.
  humanURL: https://tabby.tabbyml.com/docs/api/
  baseURL: http://localhost:8080
  tags:
  - Event
  tags_raw:
  - Events
  properties:
  - type: OpenAPI
    url: openapi/tabby-ml-events-api-openapi.yml
  - type: Documentation
    url: https://tabby.tabbyml.com/docs/welcome/
  - type: APIReference
    url: https://tabby.tabbyml.com/api/
  - type: OpenCollection
    url: collections/tabby-ml.opencollection.json
  - type: PostmanCollection
    url: collections/tabby-ml.postman_collection.json
  - type: Documentation
    url: https://tabby.tabbyml.com/docs/administration/answer-engine/
  - type: Documentation
    url: https://www.tabbyml.com/blog/doc-ingestion-api
  - type: Documentation
    url: https://tabby.tabbyml.com/docs/references/models-http-api/openai/
- aid: tabby-ml:tabby-ml-health-api
  name: Tabby Health API
  description: Server health and settings.
  humanURL: https://tabby.tabbyml.com/docs/api/
  baseURL: http://localhost:8080
  tags:
  - Health
  properties:
  - type: OpenAPI
    url: openapi/tabby-ml-health-api-openapi.yml
  - type: Documentation
    url: https://tabby.tabbyml.com/docs/welcome/
  - type: APIReference
    url: https://tabby.tabbyml.com/api/
  - type: OpenCollection
    url: collections/tabby-ml.opencollection.json
  - type: PostmanCollection
    url: collections/tabby-ml.postman_collection.json
  - type: Documentation
    url: https://tabby.tabbyml.com/docs/administration/answer-engine/
  - type: Documentation
    url: https://www.tabbyml.com/blog/doc-ingestion-api
  - type: Documentation
    url: https://tabby.tabbyml.com/docs/references/models-http-api/openai/
- aid: tabby-ml:tabby-ml-ingestion-api
  name: Tabby Ingestion API
  description: Doc ingestion into the Answer Engine knowledge base.
  humanURL: https://tabby.tabbyml.com/docs/api/
  baseURL: http://localhost:8080
  tags:
  - Ingestion
  properties:
  - type: OpenAPI
    url: openapi/tabby-ml-ingestion-api-openapi.yml
  - type: Documentation
    url: https://tabby.tabbyml.com/docs/welcome/
  - type: APIReference
    url: https://tabby.tabbyml.com/api/
  - type: OpenCollection
    url: collections/tabby-ml.opencollection.json
  - type: PostmanCollection
    url: collections/tabby-ml.postman_collection.json
  - type: Documentation
    url: https://tabby.tabbyml.com/docs/administration/answer-engine/
  - type: Documentation
    url: https://www.tabbyml.com/blog/doc-ingestion-api
  - type: Documentation
    url: https://tabby.tabbyml.com/docs/references/models-http-api/openai/
- aid: tabby-ml:tabby-ml-models-api
  name: Tabby Models API
  description: Model registry configured on the server.
  humanURL: https://tabby.tabbyml.com/docs/api/
  baseURL: http://localhost:8080
  tags:
  - Models
  properties:
  - type: OpenAPI
    url: openapi/tabby-ml-models-api-openapi.yml
  - type: Documentation
    url: https://tabby.tabbyml.com/docs/welcome/
  - type: APIReference
    url: https://tabby.tabbyml.com/api/
  - type: OpenCollection
    url: collections/tabby-ml.opencollection.json
  - type: PostmanCollection
    url: collections/tabby-ml.postman_collection.json
  - type: Documentation
    url: https://tabby.tabbyml.com/docs/administration/answer-engine/
  - type: Documentation
    url: https://www.tabbyml.com/blog/doc-ingestion-api
  - type: Documentation
    url: https://tabby.tabbyml.com/docs/references/models-http-api/openai/
- aid: tabby-ml:tabby-ml-chat-completions-api
  name: Tabby Chat Completions API
  description: OpenAI-compatible chat completions and inline chat / Answer Engine.
  humanURL: https://tabby.tabbyml.com/docs/api/
  baseURL: http://localhost:8080
  tags:
  - Chat Completions
  properties:
  - type: OpenAPI
    url: openapi/tabby-ml-chat-completions-api-openapi.yml
  - type: Documentation
    url: https://tabby.tabbyml.com/docs/welcome/
  - type: APIReference
    url: https://tabby.tabbyml.com/api/
  - type: OpenCollection
    url: collections/tabby-ml.opencollection.json
  - type: PostmanCollection
    url: collections/tabby-ml.postman_collection.json
  - type: Documentation
    url: https://tabby.tabbyml.com/docs/administration/answer-engine/
  - type: Documentation
    url: https://www.tabbyml.com/blog/doc-ingestion-api
  - type: Documentation
    url: https://tabby.tabbyml.com/docs/references/models-http-api/openai/
common:
- type: Pricing
  url: https://www.tabbyml.com/pricing
- type: CapabilityMap
  url: capabilities/tabby-ml-capability-edges.yml
  name: Tabby Business Capability Map
- type: AgenticAccess
  url: agentic-access/tabby-ml-agentic-access.yml
- type: DomainSecurity
  url: security/tabby-ml-domain-security.yml
- type: Authentication
  url: authentication/tabby-ml-authentication.yml
- type: GitHubOrganization
  url: https://github.com/TabbyML
- type: LinkedIn
  url: https://www.linkedin.com/company/tabbyml
- type: Website
  url: https://www.tabbyml.com
- type: Documentation
  url: https://tabby.tabbyml.com/docs/welcome/
- type: Plans
  url: plans/tabby-ml-plans-pricing.yml
- type: RateLimits
  url: rate-limits/tabby-ml-rate-limits.yml
- type: FinOps
  url: finops/tabby-ml-finops.yml
- url: https://www.tabbyml.com/blog
  type: Blog
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com

Tabby API — frequently asked questions

Does Tabby have an API?

Yes. APIs.io lists 6 APIs from Tabby, including Tabby Completions API, Tabby Events API and Tabby Health API, and 3 more.

Is there an OpenAPI specification for the Tabby API?

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

How do I authenticate with the Tabby API?

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

How much does the Tabby API cost?

Tabby publishes its prices; its Team plan is $19/mo per seat as of 2026-10-07. APIs.io lists 7 pricing plans for Tabby, with each plan's price, limits and inclusions under Pricing on this page.

Is the Tabby API ready for AI agents?

Tabby has a Kin Score of 32.4 out of 100 (thin) and an Agent Readiness score of 19.6 (agent-aware), scored by API Evangelist on 2026-11-06.

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