官方说明7 个来源MCP 服务8 天前
goofrey/zoom-search
Rewrite queries, zoom into source doma
在 GitHub 查看 ↗直链 · 无中转页
配置模板（请按你的客户端调整）
claude mcp add zoom-search -- npx -y zoom-search
这是根据仓库名生成的可粘贴骨架，命令行参数与包名请以该项目 README 为准。
- ★ 数取值
- 4 ★ · goofrey/zoom-search · 取自 GitHub 搜索 API · （2026-10-16 20:00:20 核对）
- 来源明细
- 收录自 punkpeye/awesome-mcp-servers 榜单（我们从中收集的条目之一） · 条目类型：MCP 服务
- 收录与活跃
- 收录于 2026-10-09 · 最近见到 2026-10-16 · 共见到 32 次 · 被 7 个来源列出
- 评分构成
- 综合分 703 · 4 ★ · 7 个来源 · mcp
常见问题（答案都来自我们的记录）
怎么安装？
我们【没有】从该仓库取到安装命令（我们的 install 覆盖率只有约 4%）。请看它的 README 或 releases 页。
它适合谁 / 用来做什么？
我们把它归在这些标签下: MCP 服务。标签来自条目自身，不是我们强加的分类。
谁维护它、还在更新吗？
仓库
goofrey/zoom-search；我们收录于 2026-10-09；最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。第三方质量标记
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
=3.10" />
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.
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
=3.10" />
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.
- 来源
- awesome · https://github.com/goofrey/zoom-search
- 按领域浏览
- MCP 服务
- Traction
- 4 ★
- 收录于
- 昨天
更多MCP 服务
所属领域与标签
每个标签都能点进去看同类的全部条目。数字是当前库里的真实条数。