MCP Tool: gemini-research — saves ~95% of research tokens
증상
Every time Claude Code uses WebSearch or WebFetch, it dumps 5,000 to 20,000+ tokens of raw HTML/markdown into the context window. On a research-heavy session (checking versions, looking up docs, comparing tools), you can burn through 50,000–100,000 tokens just on web searches — leaving less room for actual coding work.
원인
Input exceeded the model’s maximum context length, causing truncation or a refusal to process the full request. 카테고리: context-window.
해결법
I built gemini-research — an MCP server + CLI tool that delegates web research to Gemini’s free API (250 requests/day with Google Search grounding). Instead of raw web pages, Claude Code gets back ~200–400 focused tokens per query.
예상 토큰 절약
이 에러로 삽질 시: 약 5,000~15,000 토큰 소비 이 해결법 참조 시: 약 500 토큰
출처
https://github.com/anthropics/claude-code/issues/27234
Source: https://github.com/anthropics/claude-code/issues/27234
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