ferris-search

> A blazing-fast MCP server for multi-engine web search, written in Rust.

Claude Code's built-in web search works great in ideal network conditions — but in practice, many developers run into environments where it's unreliable or unavailable: corporate networks, restricted regions, air-gapped setups, or simply spotty connectivity.

While looking for a workaround, I came across open-webSearch, a Node.js MCP server that routes search queries through multiple engines. It solved the problem well. But I have a thing for Rust — and spinning up a Node.js runtime just to proxy a few HTTP requests felt heavier than it needed to be.

So I rewrote the same idea in Rust:

• No Node.js runtime — single self-contained binary, ~8 MB
• Lower latency — Rust async I/O, concurrent fan-out across engines
• Smaller footprint — negligible memory usage
• Proxy support — HTTP/SOCKS5 proxy via env var, for networks that need it

If Claude Code's search isn't working in your environment, this is for you.

ferris-search is also a good foundation for enterprise internal search scenarios. Since it's a standard MCP server written in Rust, you can fork it and add custom search engines that connect to your internal knowledge bases — Confluence, Notion, internal wikis, code repositories, or proprietary document stores.

Some ideas:

• Add an engine that searches your internal Elasticsearch or OpenSearch cluster
• Integrate with your company's Confluence or GitLab search API
• Connect to a private RAG (Retrieval-Augmented Generation) service
• Route queries to different backends based on query language or topic

With Claude Code as the AI layer and ferris-search as the search backbone, your team gets a local AI coding assistant that can actually find and reference internal documentation — without sending anything to external search engines.

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