Apple Foundation Models

Claude for Foundation Models is a Swift package that makes Claude available as a server-side language model in Apple's Foundation Models framework. The package conforms Claude to the framework's LanguageModel protocol, so you drive it with the same LanguageModelSession API you use for Apple's on-device model: respond(to:), streaming, guided generation, and tool calling all work the same way.

Requests go directly from your app to the Claude API; Apple is not in the request path and does not see prompts or responses. Usage is billed to your Anthropic account at standard API pricing. Your app decides when to use Claude and when to use Apple's on-device model: pass whichever model you want to each session.

Requirements

• iOS 27, macOS 27, visionOS 27, or watchOS 27 (all in beta): the OS releases whose Foundation Models framework supports server-side language models
• Xcode 27 (beta)
• A Claude API key from the Claude Console for development. See Authentication for production options.

Install the package

Add the package to your Package.swift:

dependencies: [
  .package(url: "https://github.com/anthropics/ClaudeForFoundationModels.git", from: "0.1.0")
]

Or in Xcode: File > Add Package Dependencies… and enter the repository URL.

Then add ClaudeForFoundationModels to your target's dependencies and import it alongside FoundationModels:

import FoundationModels
import ClaudeForFoundationModels

Quick start

ClaudeLanguageModel is the entry point. Pass it to LanguageModelSession and use the session exactly as you would with any Foundation Models provider:

import FoundationModels
import ClaudeForFoundationModels

let model = ClaudeLanguageModel(
  name: .sonnet4_6,
  auth: .apiKey(ProcessInfo.processInfo.environment["ANTHROPIC_API_KEY"] ?? "")
)

let session = LanguageModelSession(model: model)
let response = try await session.respond(to: "Plan a 4-day trip to Buenos Aires.")
print(response.content)

The initializer also accepts baseURL (default https://api.anthropic.com), timeout, and serverTools (see Server-side tools).

For a complete working program, the repository includes Examples/ClaudeExample, a runnable command-line target that streams a chat turn to the terminal, with a --search flag that enables server-side web search for the turn. Running it requires a macOS 27 host.

Choosing a model

Model identifiers are values of ClaudeModel. Use a compiled-in constant, or construct one with explicit capabilities for an ID that isn't compiled in yet (see Capabilities):

ClaudeLanguageModel(name: .opus4_8, auth: auth)

Constants mirror API model IDs (.opus4_8 is claude-opus-4-8) and carry each model's capabilities. New models ship as new constants in package releases; check ClaudeModel in Xcode for the current list, and the Models overview to compare models.

Capabilities

Each ClaudeModel declares what it accepts: sampling parameters, effort levels, adaptive thinking, structured output, and image input. The package uses this to decide which request fields to send, because sending a field a model rejects is a hard error. The constants carry the right capabilities. For an ID that isn't compiled in, declare what the model accepts (there is deliberately no shorthand that guesses):

let model = ClaudeModel(
  id: "claude-experimental-x",
  capabilities: .init(samplingParams: false, effortLevels: [.low, .high])
)
ClaudeLanguageModel(name: model, auth: auth)

Effort

Pin a Claude effort level for every request with fixedEffort:. It takes precedence over the framework's per-request reasoning hints, and it's the only way to request .xhigh or .max, because the framework's reasoning levels stop at high. The API defaults to high when no effort is sent:

ClaudeLanguageModel(name: .opus4_8, auth: auth, fixedEffort: .xhigh)

The level must be one the model accepts. Each ClaudeModel declares which of the five levels (low, medium, high, xhigh, max) its model takes, if any: some models don't accept effort at all.

When to use Claude versus the on-device model

Apple's on-device model is fast, private, and works offline, but it is sized for lightweight tasks. Escalate to Claude when you need larger context, frontier reasoning, or server-side tools such as web search and code execution. Because both use the same LanguageModelSession API, you can switch by swapping the model: argument.

Authentication

Set the credential with the auth: parameter.

API key (development)

Pass an API key directly while developing:

ClaudeLanguageModel(name: .sonnet4_6, auth: .apiKey("YOUR_API_KEY"))

Proxy (production)

For production, route requests through your own back end with .proxied. The relay at baseURL adds the Claude API credential server-side, so the app ships no key. The headers you provide are sent on every request so your proxy can authorize the caller. Pass [:] if it needs none:

ClaudeLanguageModel(
  name: .sonnet4_6,
  auth: .proxied(headers: ["X-App-Token": "..."]),
  baseURL: URL(string: "https://api.yourapp.com/claude")!
)

Your proxy receives standard Messages API requests, attaches the x-api-key header, and forwards them to https://api.anthropic.com.

Streaming

streamResponse(to:) returns the response incrementally. Each element is a cumulative snapshot of the response so far, not a delta:

let stream = session.streamResponse(to: "Summarize today's top science stories.")
for try await partial in stream {
  print(partial.content)
}

Structured output

Annotate a type with @Generable and request it with generating:. The model returns a value of that type through structured outputs:

@Generable
struct Trip {
  @Guide(description: "Destination city") var destination: String
  @Guide(description: "Length in days") var days: Int
}

let response = try await session.respond(to: "Plan a trip to Tokyo.", generating: Trip.self)
print(response.content.destination)

Structured output requires a model whose capabilities include it (all compiled-in constants do). If the chosen model does not, the package throws LanguageModelError.unsupportedGenerationGuide rather than silently degrading.

Tool use

Client-side tools

The framework's tools: array works unchanged. Conform your types to Tool, pass them to LanguageModelSession, and the framework invokes them on the device when Claude calls them. See Tool use with Claude.

let session = LanguageModelSession(model: model, tools: [FindRestaurantsTool()])

Server-side tools

Server tools (web search, web fetch, and code execution) run on Anthropic's infrastructure within a single round trip, with nothing for the framework to invoke on the device. Configure them per model with serverTools::

let model = ClaudeLanguageModel(
  name: .sonnet4_6,
  auth: auth,
  serverTools: [
    .webSearch(maxUses: 5),
    .codeExecution,
  ]
)

.webSearch and .webFetch accept optional allowedDomains, blockedDomains, and maxUses. Server tool activity surfaces in the transcript as ClaudeServerToolSegment custom segments.

Images

Models whose capabilities include image input declare the framework's vision capability. Pass image content through the framework's standard session API; the package converts it to the Claude API's image format. See Vision for image requirements.

Error handling

The package maps Claude API errors onto Apple's LanguageModelError cases where one fits: context-window overflow surfaces as .contextSizeExceeded, HTTP 429 as .rateLimited, a request past the configured timeout as .timeout. Provider errors with no framework equivalent surface as ClaudeError. Pattern-match to drive product flows:

do {
  let response = try await session.respond(to: prompt)
  print(response.content)
} catch ClaudeError.missingCredential {
  // Prompt for an API key.
} catch let error as LanguageModelError {
  // Framework-shaped errors (rate limits, guardrails, context length, decoding).
} catch {
  // Transport errors.
}

A common pattern is to catch .rateLimited and fall back to SystemLanguageModel for that turn, queue the request, or surface a retry affordance.

Feature support

The package surfaces the Messages API capabilities that the Foundation Models provider protocol can express. Features with no representation in Apple's protocol are not available through it, including:

• Prompt caching controls (the package applies prompt caching automatically; cache TTL and breakpoint placement are not configurable)
• Stop sequences
• Batch processing
• Files API
• Token counting
• Beta headers

Additional resources

The package is licensed under Apache 2.0. Bug reports are welcome through GitHub issues. External pull requests are not being accepted during the beta period.