FlexOrch MCP Server

@flexorch

代码仓库

基本信息

分类

文件与存储

传输方式

stdio

作者

flexorch

提交者

FlexOrch Dev

关于 FlexOrch MCP Server

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

FlexOrch MCP Server 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>"
      }
    }
  }
}

FlexOrch MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

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.

常见问题

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](https://app.flexorch.com).

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