AgentRunKit

A lightweight Swift 6 framework for building LLM-powered agents with type-safe tool calling.

Zero dependencies · Full Sendable · Async/await · Cloud + Local · MCP

Quick Start

import AgentRunKit

let client = OpenAIClient(apiKey: "sk-...", model: "gpt-4o", baseURL: OpenAIClient.openAIBaseURL)

let weatherTool = try Tool<WeatherParams, String, EmptyContext>(
    name: "get_weather",
    description: "Get the current weather"
) { params, _ in
    "72°F and sunny in \(params.city)"
}

let agent = Agent(client: client, tools: [weatherTool])
let result = try await agent.run(userMessage: "What's the weather in SF?", context: EmptyContext())
print(result.content)

Documentation

Full documentation including guides and API reference is available on Swift Package Index.

Installation

Add to your Package.swift:

dependencies: [
    .package(url: "https://github.com/Tom-Ryder/AgentRunKit.git", from: "1.20.1")
]

.target(name: "YourApp", dependencies: ["AgentRunKit"])

For on-device inference, additional targets are available:

• AgentRunKitMLX for MLX on Apple Silicon (requires mlx-swift-lm as a dependency)
• AgentRunKitFoundationModels for Apple Foundation Models (iOS 26+ / macOS 26+, no external dependencies)

Features

• Agent loop with configurable iteration limits and token budgets
• Streaming with AsyncThrowingStream and @Observable SwiftUI wrapper
• Type-safe tools with compile-time JSON schema validation
• Sub-agent composition with depth control and streaming propagation
• Context management: automatic compaction, pruning, token budgets
• Structured output with JSON schema constraints
• Multimodal input: images, audio, video, PDF
• Text-to-speech with concurrent chunking and MP3 concatenation
• MCP client: stdio transport, tool discovery, JSON-RPC
• Extended thinking / reasoning model support

Providers

Requirements

License

MIT License. See LICENSE for details.