Official description7 sourcesMCP servers8d ago

goofrey/zoom-search

Rewrite queries, zoom into source doma

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Config template (adjust for your client)

claude mcp add zoom-search -- npx -y zoom-search

A pasteable skeleton generated from the repository name. Check the project README for the exact package and arguments.

Star count: 4 ★ · goofrey/zoom-search · read from the GitHub search API · (checked 2026-10-16 20:00:20)
Source: collected from the punkpeye/awesome-mcp-servers list · type: MCP server
Harvest history: first seen 2026-10-09 · last seen 2026-10-16 · seen 32× · listed by 7 sources
Score: score 703 · 4 ★ · 7 sources · mcp

FAQ (answers come from our records)

How do I install it?

We did not find an install command for this repository (our install coverage is only about 4%). Check its README or releases page.

Who is it for?

We filed it under these tags: MCP 服务. The tags come from the entry itself, not a taxonomy we imposed.

Who maintains it?

repository goofrey/zoom-search；first catalogued 2026-10-09；last seen 2026-10-16。There is no official certification or quality rating here — we record sources and dates only.

Third-party quality signals

Zoom Search

以下摘录自该仓库的 README（片段） · 在 GitHub 读完整 README →

Better Answers, Bounded Extra Cost
Direct search baseline vs Zoom Search workflow
Useful results
Answer quality
Extra budget
1-5 -> 4-12 more good sources
2.0-7.2 -> 7.8-8.7 stronger final answers
+5.9s to +12.2s +2.3k to +5.1k tokens
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Quickstart ·
Agent Tool ·
Agents ·
Benchmarks ·
Advanced Configuration
Zoom Search is a search and evidence tool for AI agents. It helps agents rewrite search questions, gather broader web evidence, zoom into high-value source domains, and return sourced answers with metrics.
It is built for agentic applications that need stronger source discovery, traceability, and answer grounding than a single search call.
Why Zoom Search
- **Agent search tool**: expose structured answers, sources, warnings, and metrics for tool-calling agents.
- **Better evidence gathering**: rewrite agent questions into stronger search variants.
- **Source-domain zoom-in**: search broadly first, then focus on high-value domains.
- **Traceable outputs**: preserve source domains, duplicate provenance, warnings, and runtime metrics.
- **MCP/LangGraph ready**: use Zoom Search through MCP or LangGraph integrations.
- **Provider-flexible**: use built-in engines or custom OpenAI-compatible and native HTTP providers.
Install
Quickstart
Run a deterministic local demo without API keys:
Agent Tool Example
Install the MCP extra:
Add Zoom Search to your MCP client:
Your agent can then call the zoom_search tool with a question argument:
The tool returns sourced answers, source-domain zoom-in, warnings, and runtime metrics.
Or wrap it as a LangGraph/LangChain tool:
See docs/agent-integration.md for MCP client configuration and provider environment variables.
Benchmarks
Historical evaluations compare direct search against the Zoom Search agent workflow, showing better useful result coverage and stronger final answers with bounded extra time and token cost.
| Case | Good results | Answer quality | Extra time | Extra tokens |
|---|---:|---:|---:|---:|
| Playwright authentication reuse | 5 -> 7 | 6.6 -> 8.7 | +5.89s | +2,324 |
| GitHub Actions secrets inherit | 1 -> 4 | 2.0 -> 7.8 | +8.93s | +2,936 |
| Hydrangea pruning comparison | 4 -> 12 | 7.2 -> 8.4 | +12.17s | +5,073 |
See the full benchmark notes in docs/benchmarks.md.
Runnable examples for demo mode, streaming, conversation history, and LangGraph are available in the examples/ directory.