Local LLMs running on oMLX, MSTY, or OpenCode gain internet access through MCP search servers. Configure a hosted MCP endpoint (Scavio, Tavily) or a community extension (pi-web-access) to give Qwen, Gemma, or any local model the ability to search the web without sending queries through a cloud LLM provider.
Why MCP for local LLMs
Local models run entirely on your hardware but lack internet access. MCP bridges this gap: the model calls a search tool, the MCP server fetches results from a search API, and structured data flows back into the conversation. Your prompts and conversation history stay local; only the search queries go to the API.
oMLX MCP configuration
oMLX supports standard MCP server configuration. Add a search MCP to your oMLX config:
{
"mcpServers": {
"web-search": {
"type": "url",
"url": "https://mcp.scavio.dev/mcp",
"headers": {
"Authorization": "Bearer YOUR_SCAVIO_API_KEY"
}
}
}
}Pi extension setup
For Pi, the pi-web-access extension is the zero-config option. Install with one command and it works out of the box with Exa as the default search backend (free tier available):
pi install npm:pi-web-accessFor more control over the search backend, configure a custom MCP tool in Pi instead of using the extension. This lets you choose Tavily, Scavio, or Brave as the search provider.
MSTY configuration
MSTY supports claw-based tools. Point a MSTY claw to an MCP search endpoint or use a direct API call in a custom tool definition.
Search backend comparison for local setups
- Tavily: 1,000 free/month. Summarized results (good for grounding, less raw data). Well-supported community MCP server.
- Scavio: 250 free/month. Hosted MCP at mcp.scavio.dev/mcp. Returns structured JSON with Google, Reddit, YouTube, Amazon, TikTok. One config entry.
- Brave Search: ~1,000 free/month ($5 free credits). Raw results. Multiple community MCP implementations.
- SearXNG: Free, self-hosted. Requires running another container. Unreliable under sustained use.
Model recommendations for search-augmented workflows
From the LocalLLaMA community in May 2026: Gemma 4 31B outperforms Qwen 3.6 27B and Qwen 3.5 122B A10B for task following and prompt understanding. Qwen 3.6 35B A3B is a solid alternative on lower hardware. For search-augmented workflows, tool calling quality matters more than raw benchmark scores.