Super easy setup wizard for using Claude Code with on-premise LLMs.
Your original Claude Code configs remain intact and available while a separate config profile for on-premise LLMs will be added with CCS (Claude Code Switch). This ensures that you can keep running claude as you know it, while having a separate ccs onprem command for running Claude Code with on-premise LLMs.
Disclaimer: This is an unofficial community project. We are not affiliated with Anthropic or Claude Code in any way. We're just enthusiastic community members who love building with Claude Code and focus on privacy / sovereign AI. Read more on onprem.ai.
- Install prerequisites (if not already installed):
- Claude Code >= 2.1.72
- Node.js >= 18 (install via fnm - fast, cross-platform)
- Run setup wizard:
npx claude-code-onprem@latest- Start Claude Code with On-prem LLM:
ccs onprem- CCS Profile - Creates
~/.ccs/onprem.settings.jsonwith your LLM endpoint - Web Search MCPs - Optionally configures advanced Exa and/or Brave search MCPs
- CCS Config - Also optionally disables built-in CCS websearch when advanced search MCPs are installed
Any LLM server with Anthropic API compatibility (/v1/messages endpoint) works. Popular options:
Important: Make sure to install a version that supports the Anthropic API format. Older versions only support OpenAI-compatible endpoints.
| Server | Min Version | Pros | Cons |
|---|---|---|---|
| Ollama | v0.14.0+ | Easy setup, runs anywhere | Lower throughput, not for production |
| LM Studio | v0.4.1+ | GUI, easy model management | Desktop only, not for production |
| vLLM | v0.17.0+ | High throughput, production-ready | More complex setup |
Strong web search is critical for on-prem AI coding. On-premise LLMs are typically smaller than cloud-hosted trillion-parameter models and have less factual knowlege memorized in their weights. Solid web search with proper skill instructions acts as a form of RAG, compensating for smaller model sizes by providing access to up-to-date documentation and code examples.
Why custom search plugins? The built-in CCS web search is standardized and limited. We chose two providers: Exa for code-focused search and Brave for privacy-conscious general search. Both search plugins expose their full MCP capabilities with usage instructions (skills) optimized for agentic coding. This made a significant difference for us, though these search plugins are entirely optional.
What about privacy? With on-prem LLMs, your source code never leaves your infrastructure - that's the whole point. Web search only exposes search queries, which typically relate to external libraries and public APIs rather than your proprietary code patterns. Yes, search providers can see which technologies you're working with, which may be compliance-relevant in certain contexts. But the critical risks like source code exposure and potential credential leaks are practically eliminated when LLM processing stays on-premises.
| Provider | Strengths |
|---|---|
| Exa | Code search, API docs |
| Brave | Privacy, news/media |
The setup wizard supports command-line arguments for automation and prefilling values:
| Flag | Description |
|---|---|
--llm-url=<url> |
LLM endpoint URL |
--llm-key=<key> |
LLM API key |
--model=<name> |
Model name (skips model selection) |
--exa-key=<key> |
Exa API key |
--brave-key=<key> |
Brave API key |
-y, --yes |
Non-interactive mode (auto-approve all prompts) |
# Interactive with prefilled values
npx claude-code-onprem@latest --llm-url=http://localhost:8000/v1
# Fully non-interactive setup
npx claude-code-onprem@latest \
--llm-url=http://localhost:8000/v1 \
--llm-key=your-llm-api-key \
--model=qwen3-coder-next-80b \
--exa-key=your-exa-api-key \
-yIn non-interactive mode (-y):
- Uses provided values without prompting
- Auto-selects web search providers based on which API keys are provided
- Auto-selects the first available model if
--modelis not specified - Keeps existing plugin installations
MIT