FlexOrch MCP Server

@flexorch

リポジトリ

基本情報

カテゴリ

ファイルとストレージ

トランスポート

stdio

作者

flexorch

投稿者

FlexOrch Dev

FlexOrch MCP Server について

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 の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "flexorch": {
      "command": "flexorch-mcp",
      "env": {
        "FLEXORCH_API_KEY": "<YOUR_API_KEY>"
      }
    }
  }
}

FlexOrch MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

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.

よくある質問

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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