FlexOrch MCP Server

@flexorch

Basic information

About 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 config

Add this server to your MCP-compatible client using the configuration below.

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

FlexOrch MCP Server tools

Tool list not available yet

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We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

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.

Frequently asked questions

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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