FlexOrch

Classify documents, extract fields, mask PII, and export AI-ready datasets.

Source

Official Registry

Updated

2026-06-25

// securityCaution

Requires keys· FLEXORCH_API_KEY
Runs locally
Official / curated
Open source
Community-trusted

Running security audit…

Credentials
Network egress
Code execution
Data access
Supply chain

// install

Copy the install command and let the AI configure it · recommended for beginners

Please install the "FlexOrch" MCP server from askskill:
Run: claude mcp add 'io-github-dev-flexorch-flexorch-mcp' -- npx -y flexorch-mcp

// examples

Build a contract document dataset

Prompt

Classify the documents in this contract folder by type, extract contract ID, parties, amount, and date, automatically mask ID numbers, phone numbers, and emails, then export the results as JSONL for a RAG system.

Expected

Structured contract data grouped by type, including extracted fields, masked PII, and a JSONL file ready for RAG.

Process support forms and sensitive data

Prompt

Analyze this batch of support submission forms, identify issue categories, extract username, order number, issue summary, and submission time, and export the results after masking personal information such as names, phone numbers, and addresses.

Expected

A clearly categorized support-form dataset with key extracted fields and privacy-masked outputs.

Prepare knowledge base training data

Prompt

Convert these PDF and Word documents into knowledge-base data for AI agent retrieval, extract title, topic, source, and body summary, filter or mask sensitive information, and export everything as JSONL.

Expected

Structured document data for knowledge retrieval and training, plus a masked JSONL export.