Claude Code running via NVIDIA NIM, completely free

Features

Quick Start

Prerequisites

1. Get an API key (or use LM Studio / llama.cpp locally):
   • NVIDIA NIM: build.nvidia.com/settings/api-keys
   • OpenRouter: openrouter.ai/keys
   • DeepSeek: platform.deepseek.com/api_keys
   • LM Studio: No API key needed. Run locally with LM Studio
   • llama.cpp: No API key needed. Run llama-server locally.
2. Install Claude Code

Install uv

# Install uv (required to run the project)
pip install uv

If uv is already installed, run uv self update to get the latest version.

Clone & Configure

git clone https://github.com/codeaashu/free-claude-code.git
cd free-claude-code
cp .env.example .env

Choose your provider and edit .env:

NVIDIA_NIM_API_KEY="nvapi-your-key-here"

MODEL_OPUS=
MODEL_SONNET=
MODEL_HAIKU=
MODEL="nvidia_nim/z-ai/glm4.7"                     # fallback

# Global switch for provider reasoning requests and Claude thinking blocks.
ENABLE_THINKING=true

OPENROUTER_API_KEY="sk-or-your-key-here"

MODEL_OPUS="open_router/deepseek/deepseek-r1-0528:free"
MODEL_SONNET="open_router/openai/gpt-oss-120b:free"
MODEL_HAIKU="open_router/stepfun/step-3.5-flash:free"
MODEL="open_router/stepfun/step-3.5-flash:free"     # fallback

DEEPSEEK_API_KEY="your-deepseek-key-here"

MODEL_OPUS="deepseek/deepseek-reasoner"
MODEL_SONNET="deepseek/deepseek-chat"
MODEL_HAIKU="deepseek/deepseek-chat"
MODEL="deepseek/deepseek-chat"                      # fallback

MODEL_OPUS="lmstudio/unsloth/MiniMax-M2.5-GGUF"
MODEL_SONNET="lmstudio/unsloth/Qwen3.5-35B-A3B-GGUF"
MODEL_HAIKU="lmstudio/unsloth/GLM-4.7-Flash-GGUF"
MODEL="lmstudio/unsloth/GLM-4.7-Flash-GGUF"         # fallback

LLAMACPP_BASE_URL="http://localhost:8080/v1"

MODEL_OPUS="llamacpp/local-model"
MODEL_SONNET="llamacpp/local-model"
MODEL_HAIKU="llamacpp/local-model"
MODEL="llamacpp/local-model"

NVIDIA_NIM_API_KEY="nvapi-your-key-here"
OPENROUTER_API_KEY="sk-or-your-key-here"

MODEL_OPUS="nvidia_nim/moonshotai/kimi-k2.5"
MODEL_SONNET="open_router/deepseek/deepseek-r1-0528:free"
MODEL_HAIKU="lmstudio/unsloth/GLM-4.7-Flash-GGUF"
MODEL="nvidia_nim/z-ai/glm4.7"                      # fallback

Migration: NIM_ENABLE_THINKING was removed in this release. Rename it to ENABLE_THINKING.

ANTHROPIC_AUTH_TOKEN="your-secret-token-here"

# With authentication
ANTHROPIC_AUTH_TOKEN="your-secret-token-here" \
ANTHROPIC_BASE_URL="http://localhost:8082" claude

# claude-pick automatically uses the configured token
claude-pick

Run It

Terminal 1: Start the proxy server:

uv run uvicorn server:app --host 0.0.0.0 --port 8082

Terminal 2: Run Claude Code:

Point ANTHROPIC_BASE_URL at the proxy root URL, not http://localhost:8082/v1.

Powershell

$env:ANTHROPIC_AUTH_TOKEN="freecc"; $env:ANTHROPIC_BASE_URL="http://localhost:8082"; claude

Bash

ANTHROPIC_AUTH_TOKEN="freecc" ANTHROPIC_BASE_URL="http://localhost:8082" claude

That's it! Claude Code now uses your configured provider for free.

"claudeCode.environmentVariables": [
  { "name": "ANTHROPIC_BASE_URL", "value": "http://localhost:8082" },
  { "name": "ANTHROPIC_AUTH_TOKEN", "value": "freecc" }
]

brew install fzf        # macOS/Linux

alias claude-pick="/absolute/path/to/free-claude-code/claude-pick"

alias claude-kimi='ANTHROPIC_BASE_URL="http://localhost:8082" ANTHROPIC_AUTH_TOKEN="freecc:moonshotai/kimi-k2.5" claude'

Install as a Package (no clone needed)

uv tool install git+https://github.com/codeaashu/free-claude-code.git
fcc-init        # creates ~/.config/free-claude-code/.env from the built-in template

Edit ~/.config/free-claude-code/.env with your API keys and model names, then:

free-claude-code    # starts the server

To update: uv tool upgrade free-claude-code

How It Works

┌─────────────────┐        ┌──────────────────────┐        ┌──────────────────┐
│  Claude Code    │───────>│  Free Claude Code    │───────>│  LLM Provider    │
│  CLI / VSCode   │<───────│  Proxy (:8082)       │<───────│  NIM / OR / LMS  │
└─────────────────┘        └──────────────────────┘        └──────────────────┘
   Anthropic API                                             Native Anthropic
   format (SSE)                                             or OpenAI chat SSE

• Transparent proxy: Claude Code sends standard Anthropic API requests; the proxy forwards them to your configured provider
• Per-model routing: Opus / Sonnet / Haiku requests resolve to their model-specific backend, with MODEL as fallback
• Request optimization: 5 categories of trivial requests (quota probes, title generation, prefix detection, suggestions, filepath extraction) are intercepted and responded to locally without using API quota
• Format handling: OpenRouter, LM Studio, and llama.cpp use native Anthropic Messages endpoints; NIM and DeepSeek use shared OpenAI chat translation
• Thinking tokens: <think> tags and reasoning_content fields are converted into native Claude thinking blocks when ENABLE_THINKING=true

The proxy also exposes Claude-compatible probe routes: GET /v1/models, POST /v1/messages, POST /v1/messages/count_tokens, plus HEAD/OPTIONS support for the common probe endpoints.

Providers

Models use a prefix format: provider_prefix/model/name. An invalid prefix causes an error.

Discord Bot

Control Claude Code remotely from Discord (or Telegram). Send tasks, watch live progress, and manage multiple concurrent sessions.

Capabilities:

• Tree-based message threading: reply to a message to fork the conversation
• Session persistence across server restarts
• Live streaming of thinking tokens, tool calls, and results
• Unlimited concurrent Claude CLI sessions (concurrency controlled by PROVIDER_MAX_CONCURRENCY)
• Voice notes: send voice messages; they are transcribed and processed as regular prompts
• Commands: /stop (cancel a task; reply to a message to stop only that task), /clear (reset all sessions, or reply to clear a branch), /stats

Setup

1. Create a Discord Bot: Go to Discord Developer Portal, create an application, add a bot, and copy the token. Enable Message Content Intent under Bot settings.

2. Edit .env:

MESSAGING_PLATFORM="discord"
DISCORD_BOT_TOKEN="your_discord_bot_token"
ALLOWED_DISCORD_CHANNELS="123456789,987654321"

Enable Developer Mode in Discord (Settings → Advanced), then right-click a channel and "Copy ID". Comma-separate multiple channels. If empty, no channels are allowed.

3. Configure the workspace (where Claude will operate):

CLAUDE_WORKSPACE="./agent_workspace"
ALLOWED_DIR="C:/Users/yourname/projects"

4. Start the server:

uv run uvicorn server:app --host 0.0.0.0 --port 8082

5. Invite the bot via OAuth2 URL Generator (scopes: bot, permissions: Read Messages, Send Messages, Manage Messages, Read Message History).

Telegram

Set MESSAGING_PLATFORM=telegram and configure:

TELEGRAM_BOT_TOKEN="123456789:ABCdefGHIjklMNOpqrSTUvwxYZ"
ALLOWED_TELEGRAM_USER_ID="your_telegram_user_id"

Get a token from @BotFather; find your user ID via @userinfobot.

Voice Notes

Send voice messages on Discord or Telegram; they are transcribed and processed as regular prompts.

Install the voice extras:

# If you cloned the repo:
uv sync --extra voice_local          # Local Whisper
uv sync --extra voice                # NVIDIA NIM
uv sync --extra voice --extra voice_local  # Both

# If you installed as a package (no clone):
uv tool install "free-claude-code[voice_local] @ git+https://github.com/codeaashu/free-claude-code.git"
uv tool install "free-claude-code[voice] @ git+https://github.com/codeaashu/free-claude-code.git"
uv tool install "free-claude-code[voice,voice_local] @ git+https://github.com/codeaashu/free-claude-code.git"

Configure via WHISPER_DEVICE (cpu | cuda | nvidia_nim) and WHISPER_MODEL. See the Configuration table for all voice variables and supported model values.

Configuration

Core

Rate Limiting & Timeouts

Messaging & Voice

See .env.example for all supported parameters.

Development

Project Structure

free-claude-code/
├── server.py              # Entry point
├── api/                   # FastAPI routes, API service layer, model routing, request detection, optimizations
├── core/                  # Shared Anthropic protocol helpers, SSE, conversion, parsers, token counting
├── providers/             # Provider registry, scoped runtime state, OpenAI chat + Anthropic messages transports
├── messaging/             # MessagingPlatform ABC + Discord/Telegram bots, commands, voice, session management
├── config/                # Settings, NIM config, logging
├── cli/                   # CLI session and process management
└── tests/                 # Pytest test suite

Commands

uv run ruff format     # Format code
uv run ruff check      # Lint
uv run ty check        # Type checking
uv run pytest          # Run tests

Extending

Adding an OpenAI-compatible provider (Groq, Together AI, etc.) — extend OpenAIChatTransport, then add a descriptor in the provider registry:

from providers.openai_compat import OpenAIChatTransport
from providers.base import ProviderConfig

class MyProvider(OpenAIChatTransport):
    def __init__(self, config: ProviderConfig):
        super().__init__(config, provider_name="MYPROVIDER",
                         base_url="https://api.example.com/v1", api_key=config.api_key)

Adding a native Anthropic provider — extend AnthropicMessagesTransport, then add a descriptor in providers.registry.

Adding a fully custom provider — extend BaseProvider directly, implement stream_response(), and register its descriptor.

Adding a messaging platform — extend MessagingPlatform in messaging/ and implement start(), stop(), send_message(), edit_message(), and on_message().

Contributing

• Report bugs or suggest features via Issues
• Add new LLM providers (Groq, Together AI, etc.)
• Add new messaging platforms (Slack, etc.)
• Improve test coverage
• Not accepting Docker integration PRs for now

git checkout -b my-feature
uv run ruff format && uv run ruff check && uv run ty check && uv run pytest
# Open a pull request

License

MIT License. See LICENSE for details.

Built with FastAPI, OpenAI Python SDK, discord.py, and python-telegram-bot.

Cooked by aashuu ✦ (Ashutosh Kumar)
Founder of 2C Labs

I build tech businesses through SaaS products across every layer of the internet ( Web2 ▪︎ Web3 ▪︎ AI-native ▪︎ Infrastructure )

Connect here:
Website www.aashuu.me ✦ 𝕏 @warrioraashuu ✦ LinkedIn @warrioraashuu