Open-source Deep Research
AutoSearch vs SerpAPI — MCP-Native Open-Source Alternative
Use AutoSearch when SerpAPI's per-search billing or single-channel model gets in the way.
01
Multi-channel vs single-engine
SerpAPI scrapes Google / Bing / Yandex / Baidu pages and returns SERP JSON. AutoSearch goes further: web, GitHub, Stack Overflow, arxiv, Reddit, Hacker News, dev.to, YouTube, Bilibili, plus 10+ Chinese ecosystem sources. One query covers what would otherwise take a stack of integrations.
02
MCP-native integration
SerpAPI is plain HTTP — every host wires its own client. AutoSearch ships an MCP server. Claude Code, Cursor, Cline, GPT-Researcher, and any other MCP-aware host connect with a one-line config; agents call research tools directly inside the reasoning loop.
03
Free open source vs metered API
SerpAPI charges per search request. AutoSearch is MIT-licensed and free for self-host; only the channels you enable that require their own keys (e.g. high-rate-limit GitHub) carry external cost. This makes large research runs and CI-gated evaluations cheap.
How it fits
AutoSearch replaces SerpAPI when research goes beyond plain SERP scraping — when agents need GitHub, arxiv, Reddit, Chinese sources, or video transcripts in the same workflow. SerpAPI remains useful for narrow SERP-only tasks (rank tracking, AdWords analysis) where you only need Google's result page. For deep research and AI agent workflows, AutoSearch's multi-channel + MCP-native design is the better fit.
Try this prompt
Replace a SerpAPI-based research script with AutoSearch.
Keep the same query, but return cited results from web + GitHub + Hacker News + Zhihu in one run.