Continue
Continue is the open-source AI code assistant for VS Code and JetBrains, distributed under Apache 2.0. The Continue IDE extensions and the Continue CLI federate to any LLM provider — Anthropic, OpenAI, Mistral, OpenRouter, Ollama, and a Continue-managed proxy — and load their configuration from Continue Hub. Continue Hub (api.continue.dev) is the registry and IDE API that serves assistants, blocks, models, rules, prompts, docs, and MCP servers to the extensions, along with free-trial status, organization policy, secrets sync, and the Stripe checkout URL for the Models Add-On. Continue has also pivoted into "continuous AI" — source- controlled checks that live as markdown files under .continue/checks/ and run in CI as GitHub status checks.
Solid contracts, transparent operations, and an easy start — typically complete on four or five facets with one clear soft spot.
API Evangelist profiles Continue the way a machine reads it — 65 machine-readable artifacts across 5 APIs, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — Continue scores 61.8/100 (strong), with a separate agent-readiness read of 55/100 (agent ready). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Kin Score
This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.
Kin Score
How this is scored →scored 2026-07-27 · rubric v0.5
How we profile Continue
Each block below is one kind of artifact we hold for Continue. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.
APIs 5
Each API is captured as its own OpenAPI definition — every operation, parameter, and response. This is the single most useful machine-readable description of what an API does, and it's what lets us score, lint, mock, and generate against it without asking the provider for anything.
Individual APIs this provider publishes, each with its own machine-readable definition.
Continue IDE Extensions
Open-source IDE plugins shipping for VS Code and JetBrains. Provide chat, edit, apply, autocomplete, and agent modes. Bring your own LLM (Anthropic, OpenAI, Mistral, OpenRouter,...
Continue CLI
Open-source command-line interface powering Continue's source-controlled AI checks. Checks are markdown files in .continue/checks/ that run as full AI agents against pull reques...
Continue Hub
Hosted registry where teams publish and share assistants, blocks (models, rules, prompts, docs, MCP servers, context providers), and policy. Powers the Continue Hub IDE API and ...
Continue Mission Control
Observability surface for tracking check outcomes, agent runs, and adoption metrics across an organization's repositories. Part of the Team and Company tiers.
Continue Ide API
The Ide API from Continue — 8 operation(s) for ide.
Open Collections 1
Open, tool-agnostic collections carry the same runnable value as Postman without locking you to one client — the portable, forkable form of the same exercise.
Open, tool-agnostic API collections (OpenAPI-derived and Bruno).
Continue Hub IDE API
OPEN COLLECTIONPricing Plans 1
Pricing is part of the interface. Machine-readable plans tell you what a tier costs and includes before you commit — one of the six things the Kin Score reads for commercial clarity.
Published pricing tiers and plan structures.
Rate Limits 1
Rate limits are the difference between a demo that works and a production integration that doesn't fall over. Publishing them is an operational-transparency signal — and a hard requirement for any agent that plans its own throughput.
Documented rate limits and quota policies.
Continue Dev Rate Limits
RATE LIMITSFinOps 1
Cost, billing, and metering signals let a buyer model the financial operations of an API before it's live. We profile them for the same reason we profile pricing: the money is part of the contract.
Cost, billing, and metering signals for API financial operations.
Continue Dev Finops
FINOPSFeatures 21
The notable capabilities this provider advertises, captured as structured features so they can be searched and compared instead of read one landing page at a time.
Notable capabilities this provider offers.
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Semantic Vocabularies 1
JSON-LD contexts give the data shared meaning across APIs. We profile them because semantics are what let a machine reconcile 'customer' here with 'customer' somewhere else.
JSON-LD contexts and semantic vocabularies used across these APIs.
Continue Dev Context
JSON-LDSpectral Rules 2
Governance rulesets we run against this provider's specs — the automated checks behind parts of the score. Profiling them makes the quality bar explicit and re-runnable, not a matter of opinion.
Continue API Rules
SPECTRALContinue API Rules
SPECTRALJSON Schema 3
Standalone JSON Schema definitions describe the data models behind the API. We profile them so the shapes are validatable on their own — useful long after a single request is forgotten.
Standalone JSON Schema definitions for this provider's data models.
Continue Hub Assistant
JSON SCHEMAContinue Free Trial Status
JSON SCHEMAContinue Hub Organization
JSON SCHEMAJSON Structure 1
JSON Structure captures the data shapes in a form built for tooling — a complement to JSON Schema that keeps the model machine-legible.
JSON Structure definitions describing this provider's data shapes.
Continue Dev Assistant Structure
JSON STRUCTUREExamples 2
Real request and response payloads are what turn a spec from abstract into obvious — and they're one of the twelve things an agent needs to call an API correctly on the first try.
Example request and response payloads for these APIs.
Security Posture 2
Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Agentic Access 1
An x-agentic-access contract marks which operations are safe for an agent to run on its own and which need a human in the loop. It is the difference between an API an agent can use and one it can use safely.
Recommended x-agentic-access execution contracts for AI agents.
Use Cases 8
What developers actually build with this provider — captured so the catalogue answers 'what is this for', not just 'what does this expose'.
What developers build with this provider.
In-editor AI chat, edit, and apply
Use any frontier or local model directly inside VS Code and JetBrains without lock-in to one vendor.
Source-controlled coding standards enforced in CI
Define checks as markdown in .continue/checks/, have AI enforce them on every PR, see results as GitHub status checks.
Team-shared assistants
Publish assistants on Continue Hub so every engineer pulls the same models, rules, prompts, docs, and MCP servers.
BYO LLM cost control
Federate to a self-hosted Ollama, an OpenRouter account, or your own Anthropic/OpenAI key to keep AI spend on your existing provider.
On-prem prompt isolation
Route model traffic through an on-prem Continue proxy so prompts and secrets never leave the corporate network.
Local autocomplete with Ollama
Run code completion against a local model for zero-egress, zero-cost inference.
MCP tool integration
Compose MCP servers into a Continue assistant to give the agent access to internal tools without writing extension code.
Continuous AI
Apply Continue's "standards as checks" model to legacy codebases — codify standards in markdown, then have AI agents drag the codebase toward them.
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Integrations 12
Pre-built integrations with other platforms tell you where this provider already fits in a stack.
Pre-built integrations with other platforms and tools.
Anthropic
Use Claude Opus, Sonnet, and Haiku as the chat/edit/apply/autocomplete model inside Continue. Anthropic-continue-hub publishes ready-to-use blocks.
OpenAI
Use GPT-class models as Continue model providers via openai-continue-hub.
Mistral
mistral-continue-hub publishes Mistral models as Continue blocks.
OpenRouter
openrouter-continue-hub federates to any OpenRouter-hosted model.
Ollama
ollama-continue-hub points Continue at a local Ollama server for zero-egress inference.
AWS Bedrock
bedrock-continue-hub uses Bedrock-hosted models, including Claude on Bedrock.
google-continue-hub federates to Gemini and Vertex AI models.
Together AI, xAI, Cerebras, SambaNova, Cohere, IBM watsonx, Novita, NCompass, Inception Labs, Relace, IONOS
Per-provider Continue Hub repositories ship blocks for each.
GitHub
Continue checks run in CI and report status checks back to the GitHub PR. The check-cli, checks-cli, and suggestions-cli automate these flows.
Slack, Sentry, Snyk
Starter tier and above can connect Continue agents to Slack, Sentry, and Snyk.
Docker
docker-continue-hub publishes Docker-authored blocks for Continue.
Model Context Protocol
Continue assistants compose MCP servers as tool sources; Continue maintains a fork of the official MCP TypeScript SDK.
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Solutions 3
Packaged solutions the provider offers on top of the raw API surface.
Packaged solutions this provider offers.
Continuous AI for engineering teams
Codify coding standards as markdown checks; AI agents enforce them in CI on every pull request.
Open-source AI IDE for any LLM
Drop-in replacement for proprietary AI coding assistants without surrendering model choice or telemetry control.
Hub-managed assistant distribution
Centralize team assistants on Continue Hub instead of per-engineer config sprawl.
Resources
Every other property we hold for Continue — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.
Get Started 3
Portal, sign-up, and the first successful call
Documentation 4
Reference material describing how the API behaves
Agent Surfaces 2
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 2
Pagination, idempotency, versioning, errors, and events
Build 16
SDKs, sample code, and the tooling you integrate with
Scroll within the panel for all 16 ·
Access & Security 2
Authentication, authorization, and security posture
Operate 1
Status, limits, changes, and where to get help
Commercial 4
Pricing, plans, and the legal terms of use
Company 3
The organization behind the API
Other 1
Properties that don't map to a standard resource type
← All providers · Data indexed from github.com/api-evangelist/continue-dev · machine-readable index on apis.io