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apfel

The free AI already on your Mac.

Version 1.0.1 Swift 6.3+ macOS 26 Tahoe+ No Xcode Required License: MIT 100% On-Device Website #agentswelcome

Every Mac with Apple Silicon ships a built-in language model as part of Apple Intelligence. apfel gives you access to it — from the terminal, as a local OpenAI-compatible server, or as an interactive chat. No API keys, no cloud, no downloads. It's already on your machine.

What It Is

Every Apple Silicon Mac with Apple Intelligence includes Apple's on-device foundation model. apfel exposes it through https://developer.apple.com/documentation/foundationmodels so you can use it directly from the shell and from OpenAI-compatible clients.

Mode Command What you get
UNIX tool apfel "prompt" / echo "text" | apfel Pipe-friendly answers, file attachments, JSON output, exit codes
OpenAI-compatible server apfel --serve Drop-in local http://localhost:11434/v1 backend for OpenAI SDKs
Command-line chat apfel --chat Multi-turn chat with context-window management

Tool calling works across CLI, chat, and server. Inference stays 100% on-device. The context window is 4096 tokens.

apfel CLI

Requirements & Install

  • macOS 26 Tahoe or newer, Apple Silicon (M1+), and Apple Intelligence enabled: https://support.apple.com/en-us/121115
  • Building from source requires Command Line Tools with the macOS 26.4 SDK (Swift 6.3). No Xcode required.

Homebrew (recommended):

brew install apfel
brew upgrade apfel

Latest release immediately via tap: brew install Arthur-Ficial/tap/apfel (homebrew-core autobump can lag up to 24h).

Build from source:

git clone https://github.com/Arthur-Ficial/apfel.git
cd apfel
make install

Update with brew upgrade apfel or apfel --update. Troubleshooting and Apple Intelligence setup notes: docs/install.md.

Quick Start

UNIX tool

Shell note: if your prompt contains !, prefer single quotes in zsh/bash so history expansion does not break copy-paste. Example: apfel 'Hello, Mac!'

# Single prompt
apfel "What is the capital of Austria?"

# Permissive mode -- reduces guardrail false positives for creative/long prompts
apfel --permissive "Write a dramatic opening for a thriller novel"

# Stream output
apfel --stream "Write a haiku about code"

# Pipe input
echo "Summarize: $(cat README.md)" | apfel

# Attach file content to prompt
apfel -f README.md "Summarize this project"

# Attach multiple files
apfel -f old.swift -f new.swift "What changed between these two files?"

# Combine files with piped input
git diff HEAD~1 | apfel -f CONVENTIONS.md "Review this diff against our conventions"

# JSON output for scripting
apfel -o json "Translate to German: hello" | jq .content

# System prompt
apfel -s "You are a pirate" "What is recursion?"

# System prompt from file
apfel --system-file persona.txt "Explain TCP/IP"

# Quiet mode for shell scripts
result=$(apfel -q "Capital of France? One word.")

OpenAI-compatible server

apfel --serve                              # foreground
brew services start apfel                  # background (like Ollama)

Then in another terminal:

curl http://localhost:11434/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{"model":"apple-foundationmodel","messages":[{"role":"user","content":"Hello"}]}'

Works with the official Python client:

from openai import OpenAI

client = OpenAI(base_url="http://localhost:11434/v1", api_key="unused")
resp = client.chat.completions.create(
    model="apple-foundationmodel",
    messages=[{"role": "user", "content": "What is 1+1?"}],
)
print(resp.choices[0].message.content)

Run in background (auto-restarts, starts at login - docs/background-service.md):

brew services start apfel
brew services stop apfel
APFEL_TOKEN=$(uuidgen) APFEL_MCP=/path/to/tools.py brew services start apfel

Interactive chat

apfel --chat
apfel --chat -s "You are a helpful coding assistant"
apfel --chat --mcp ./mcp/calculator/server.py      # chat with MCP tools
apfel --chat --debug                                # debug output to stderr

Ctrl-C exits cleanly. Context window is managed automatically with configurable strategies (docs/context-strategies.md).

Demos

See demo/ for real-world shell scripts powered by apfel.

cmd — natural language to shell command:

demo/cmd "find all .log files modified today"
# $ find . -name "*.log" -type f -mtime -1

demo/cmd -x "show disk usage sorted by size"   # -x = execute after confirm
demo/cmd -c "list open ports"                   # -c = copy to clipboard

Shell function version — add to your .zshrc and use cmd from anywhere:

# cmd - natural language to shell command (apfel). Add to .zshrc:
cmd(){ local x c r a; while [[ $1 == -* ]]; do case $1 in -x)x=1;shift;; -c)c=1;shift;; *)break;; esac; done; r=$(apfel -q -s 'Output only a shell command.' "$*" | sed '/^```/d;/^#/d;s/\x1b\[[0-9;]*[a-zA-Z]//g;s/^[[:space:]]*//;/^$/d' | head -1); [[ $r ]] || { echo "no command generated"; return 1; }; printf '\e[32m$\e[0m %s\n' "$r"; [[ $c ]] && printf %s "$r" | pbcopy && echo "(copied)"; [[ $x ]] && { printf 'Run? [y/N] '; read -r a; [[ $a == y ]] && eval "$r"; }; return 0; }
cmd find all swift files larger than 1MB     # shows: $ find . -name "*.swift" -size +1M
cmd -c show disk usage sorted by size        # shows command + copies to clipboard
cmd -x what process is using port 3000       # shows command + asks to run it
cmd list all git branches merged into main
cmd count lines of code by language

oneliner — complex pipe chains from plain English:

demo/oneliner "sum the third column of a CSV"
# $ awk -F',' '{sum += $3} END {print sum}' file.csv

demo/oneliner "count unique IPs in access.log"
# $ awk '{print $1}' access.log | sort | uniq -c | sort -rn

mac-narrator — your Mac's inner monologue:

demo/mac-narrator              # one-shot: what's happening right now?
demo/mac-narrator --watch      # continuous narration every 60s

Also in demo/:

  • wtd — "what's this directory?" instant project orientation
  • explain — explain a command, error, or code snippet
  • naming — naming suggestions for functions, variables, files
  • port — what's using this port?
  • gitsum — summarize recent git activity

Longer walkthroughs: docs/demos.md.

MCP Tool Support

Attach Model Context Protocol tool servers with --mcp. apfel discovers tools, executes them automatically, and returns the final answer. No glue code needed.

apfel --mcp ./mcp/calculator/server.py "What is 15 times 27?"
mcp: ./mcp/calculator/server.py - add, subtract, multiply, divide, sqrt, power    ← stderr
tool: multiply({"a": 15, "b": 27}) = 405                                          ← stderr
15 times 27 is 405.                                                                ← stdout

Tool info goes to stderr; only the answer goes to stdout. Use -q to suppress tool info.

apfel --mcp ./server_a.py --mcp ./server_b.py "Use both tools"  # multiple servers
apfel --serve --mcp ./mcp/calculator/server.py                   # server mode
apfel --chat --mcp ./mcp/calculator/server.py                    # chat mode

Ships with a calculator MCP server at mcp/calculator/. See docs/mcp-calculator.md for details.

Remote MCP servers (Streamable HTTP transport, MCP spec 2025-03-26):

# Remote MCP server over HTTPS
apfel --mcp https://mcp.example.com/v1 "what tools do you have?"

# With bearer token auth - prefer the env var (flag is visible in ps aux)
APFEL_MCP_TOKEN=mytoken apfel --mcp https://mcp.example.com/v1 "..."
apfel --mcp https://mcp.example.com/v1 --mcp-token mytoken "..."

# Mixed local + remote
apfel --mcp /path/to/local.py --mcp https://remote.example.com/v1 "..."

Security: Use APFEL_MCP_TOKEN env var rather than --mcp-token — CLI flags are visible in ps aux. apfel refuses to send a bearer token over plaintext http:// (use https://).

Ready-made MCPs. apfel-mcp.franzai.com ships three token-budget-optimized MCP servers designed for apfel's 4096-token window: url-fetch (Readability article extraction with SSRF guards), ddg-search (DuckDuckGo web search, no API key), and the flagship compound search-and-fetch tool. Install with brew install Arthur-Ficial/tap/apfel-mcp. The repo is open for contributions of new apfel-optimized MCPs — rules at apfel-mcp.franzai.com/#contribute.

OpenAI API Compatibility

Base URL: http://localhost:11434/v1

Feature Status Notes
POST /v1/chat/completions Supported Streaming + non-streaming
GET /v1/models Supported Returns apple-foundationmodel
GET /health Supported Model availability, context window, languages
GET /v1/logs, /v1/logs/stats Debug only Requires --debug
Tool calling Supported Native ToolDefinition + JSON detection. See docs/tool-calling-guide.md
response_format: json_object Supported Via system prompt injection
temperature, max_tokens, seed Supported Mapped to GenerationOptions
stream: true Supported SSE with usage stats in final chunk
finish_reason Supported stop, tool_calls, length
Context strategies Supported x_context_strategy, x_context_max_turns, x_context_output_reserve extension fields
CORS Supported Enable with --cors
POST /v1/completions 501 Legacy text completions not supported
POST /v1/embeddings 501 Embeddings not available on-device
logprobs=true, n>1, stop, presence_penalty, frequency_penalty 400 Rejected explicitly. n=1 and logprobs=false are accepted as no-ops
Multi-modal (images) 400 Rejected with clear error
Authorization header Supported Required when --token is set. See docs/server-security.md

Full API spec: openai/openai-openapi.

Limitations

Constraint Detail
Context window 4096 tokens (input + output combined)
Platform macOS 26+, Apple Silicon only
Model One model (apple-foundationmodel), not configurable
Guardrails Apple's safety system may block benign prompts. --permissive reduces false positives (docs/PERMISSIVE.md)
Speed On-device, not cloud-scale — a few seconds per response
No embeddings / vision Not available on-device

Reference Docs

Architecture

CLI (single/stream/chat) ──┐
                           ├─→ FoundationModels.SystemLanguageModel
HTTP Server (/v1/*) ───────┘   (100% on-device, zero network)
                                ContextManager → Transcript API
                                SchemaConverter → native ToolDefinitions
                                TokenCounter → real token counts (SDK 26.4)

Swift 6.3 strict concurrency. Three targets: ApfelCore (pure logic, unit-testable), apfel (CLI + server), and apfel-tests (pure Swift runner, no XCTest).

Build & Test

make install                             # build release + install to /usr/local/bin
make build                               # build release only
make version                             # print current version
make release-minor                       # bump minor: 0.6.x -> 0.7.0
swift build                              # quick debug build (no version bump)
swift run apfel-tests                    # unit tests
python3 -m pytest Tests/integration/ -v  # integration tests
apfel --benchmark -o json                # performance report

.version is the single source of truth. Only make release (via CI) bumps versions. Local builds do not change the version.

The apfel tree

Everything that grows out of apfel. Each project ships as its own repo, its own landing page, and its own Homebrew formula or cask.

Trunk

Apps

Extensions

  • apfel-mcp — three token-budget-optimized MCP servers for apfel's 4096-token context window: url-fetch (Readability article extraction with SSRF guards), ddg-search (DuckDuckGo web search, no API key), and the flagship compound search-and-fetch tool. Open for contributions of more apfel-optimized MCPs.

  • apfel-gui — native SwiftUI debug inspector for apfel with request timeline, MCP protocol viewer, chat, and TTS/STT. Built for developers who want to watch exactly what apfel sends to the model.

Community Projects

Built something on top of apfel? Open an issue and it can be added here.

Contributing

Bug reports, feature ideas, pull requests, and new community projects all welcome. Open an issue or a PR on the relevant repo.

#agentswelcome — AI agent contributions are welcome across the entire apfel tree — apfel itself and every Arthur-Ficial/apfel-* repo. Claude Code, Codex, Cursor, Aider, any autonomous coding agent: if you can read the repo's CLAUDE.md, run the tests, and open a pull request, you can contribute. Credit your tool in the commit trailer (e.g. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>), include a passing test suite, and submit. Humans and agents are reviewed on the same bar: clean code, passing tests, honesty about limits.

The most agent-friendly entry point is apfel-mcp — its contribution rules and idea list at apfel-mcp.franzai.com/#contribute are written to be unambiguous enough for an agent to follow without human translation.

License

MIT

About

The free AI already on your Mac. CLI tool, OpenAI-compatible server, and interactive chat — all on-device via Apple Intelligence. No API keys, no cloud, no downloads.

apfel.franzai.com

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macos swift cli homebrew unix on-device apple-silicon llm apple-intelligence tool-calling openai-compatible macos-26 foundationmodels

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