Agentic Document Parsing and Extraction (ADP)
@Laiye-ADP
关于 Agentic Document Parsing and Extraction (ADP)
ADP integrates Vision-Language Models (VLM), Large Language Models (LLM) and autonomous agent decision-making technologies. It reshapes traditional document processing by transforming conventional rule-based field extraction into goal-driven end-to-end intelligent automation. Foc
基本信息
配置
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"laiye-adp": {
"command": "npx",
"args": [
"-y",
"@laiye-adp/mcp"
],
"env": {
"ADP_API_KEY": "your-adp-api-key"
}
}
}
}工具
未检测到工具
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
概览
What is Agentic Document Parsing and Extraction (ADP)?
A Model Context Protocol server that connects MCP-compatible AI clients to Laiye’s Agentic Document Processing platform, enabling automated document parsing and key field extraction using VLM, LLM, and autonomous agents. It handles overseas and domestic invoices, contracts, financial statements, and certificates without requiring template setup or rule maintenance.
How to use Agentic Document Parsing and Extraction (ADP)?
Sign up at adp-global.laiye.com, retrieve an API key, then configure your MCP client with the Streamable HTTP endpoint https://adp.laiye.com/mcp?key=<YOUR-ADP-API-Key>. Once connected, describe your document processing task in natural language.
Key features of Agentic Document Parsing and Extraction (ADP)
- Parse PDFs, images, Office documents into structured text and tables
- Extract fields from global invoices, receipts, and purchase orders
- Extract fields from Chinese ID cards, driver licenses, and passports
- Use custom extraction apps created on the ADP platform
- Process documents synchronously or asynchronously
- Accept file via URL or Base64 encoding
Use cases of Agentic Document Parsing and Extraction (ADP)
- Automate cross-border invoice processing for accounts payable
- Extract order details from purchase orders for supply chain reconciliation
- Parse and extract data from Chinese ID cards for identity verification
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