review-gate-mcp
An MCP server that extracts fields from documents and holds uncertain extractions for human review, ensuring high confidence data flows automatically while uncertain cases are resolved manually.
README
review-gate-mcp
An MCP server that asks a human when it isn't sure.
Most extraction demos guess. This one implements the pattern that makes automation safe to run on documents that matter: fields extracted with high confidence flow through; anything uncertain is held in a review queue for a person to resolve - never silently guessed into your systems.
document ──▶ extract_with_gate ──▶ confident fields ──▶ your system
│
└──▶ uncertain fields ──▶ review_queue ──▶ a human ──▶ resolve_review
Tools
| tool | what it does |
|---|---|
extract_with_gate |
extract invoice_number, total_amount, date, email, vendor_name from text; confidence below 0.85 goes to the queue instead of the output |
review_queue |
list items waiting for a human decision |
resolve_review |
a human supplies the verified value, closing the loop |
Run it
npm install
npm test # end-to-end over real MCP stdio: extract -> hold -> human resolve
Add to Claude Code / Claude Desktop / Cursor (any MCP client):
{
"mcpServers": {
"review-gate": { "command": "node", "args": ["/path/to/review-gate-mcp/server.js"] }
}
}
Then ask your agent to extract fields from a pasted document and watch what it does with the smudged one.
The point
The extractors here are deliberately transparent heuristics - swap in a model-backed extractor and the gate stays identical. The pattern is the product: a system that escalates its hard cases beats one that guesses them. This is the standard RavnLab builds automation to; the evaluation side of the same idea lives in ravnlab-eval-harness.
MIT. Built by RavnLab.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。