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FlexOrch MCP

@flexorch

代码仓库

关于 FlexOrch MCP

FlexOrch MCP converts unstructured documents (PDF, DOCX, invoices, contracts, payroll) into structured, LLM-ready datasets via 6 async tools. Covers the full pipeline: classify → extract fields → mask PII → export JSONL or RAG chunks, with PII detection across 10+ locales (TR, DE

#document-processing#pii#extraction#llm-dataset#rag#classification

基本信息

分类

文件与存储

传输方式

stdio

发布者

flexorch

提交者

FlexOrch Dev

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "flexorch": {
      "command": "flexorch-mcp",
      "env": {
        "FLEXORCH_API_KEY": "<YOUR_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 FlexOrch MCP?

FlexOrch gives AI agents a native way to process business documents end-to-end — no custom parsing code needed.

How to use FlexOrch MCP?

Install with pip install flexorch-mcp, then configure an MCP server entry with your API key in the FLEXORCH_API_KEY environment variable. Invoke any of the six tools (e.g., process_document, extract_fields) from your AI client.

Key features of FlexOrch MCP

  • Submit a document URL and receive a job ID.
  • Poll job status with poll_job.
  • Get document classification and quality scores.
  • Extract structured fields from documents.
  • Detect and mask PII in 10+ locales.
  • Export results as JSONL or RAG chunks.

Use cases of FlexOrch MCP

  • Process invoices, contracts, or forms end-to-end without manual parsing.
  • Classify incoming documents and assess their quality.
  • Extract specific fields (e.g., dates, amounts) from scanned documents.
  • Mask personally identifiable information before sharing documents.
  • Export processed data for downstream systems or vector database ingestion.

FAQ from FlexOrch MCP

What does FlexOrch MCP do for AI agents?

It lets AI agents process business documents end-to-end, including submission, classification, field extraction, PII masking, and export — without writing custom parsing code.

How do I install FlexOrch MCP?

Run pip install flexorch-mcp in your Python environment.

How do I configure the server?

Add a flexorch entry under mcpServers in your MCP configuration, set the command to flexorch-mcp, and provide your API key via the FLEXORCH_API_KEY environment variable.

What tools are available?

Six tools: process_document, poll_job, get_document_info, extract_fields, mask_pii, and export_dataset.

Where do I get an API key?

Get your API key at app.flexorch.com.

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