flexorch-mcp

MCP server for FlexOrch — SDK for machines.

Connect Claude and other MCP-compatible agents to the FlexOrch document intelligence pipeline. Process documents, extract structured data, detect PII, and export LLM-ready datasets — all through natural language tool calls.

What this is

flexorch-mcp is a thin proxy that exposes the FlexOrch API as MCP tools. All processing happens on FlexOrch's managed infrastructure. A FlexOrch account and API key are required.

For humans writing code: use flexorch-sdk (Python) or flexorch-sdk-js (TypeScript).
For agents: use this package.

Tools

Tool	Description
`document.process`	Upload and process a document (PDF, DOCX, TXT, XLSX, HTML, XML, EML, JPG, PNG, TIFF)
`document.reprocess`	Re-queue an already-uploaded document through the pipeline
`job.status`	Poll a processing job until completed or failed
`job.result`	Get structured extracted fields from a completed job
`dataset.build`	Build a structured dataset from a completed execution
`dataset.search`	Semantic search across indexed datasets (Pro+)
`dataset.export`	Export a dataset as JSONL, CSV, JSON, XML, MD, or RAG (LangChain/LlamaIndex chunks)
`dataset.index`	Trigger semantic vector indexing for a dataset (Pro+)
`dataset.chunks`	Retrieve paginated RAG-ready text chunks from an indexed dataset (Pro+)

Installation

Terminal

pip install flexorch-mcp

Requires Python 3.10+.

Configuration

Claude Desktop

Add to your Claude Desktop config file (create it if it doesn't exist):

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json

config.json

{
  "mcpServers": {
    "flexorch": {
      "command": "flexorch-mcp",
      "env": {
        "FLEXORCH_API_KEY": "dfx_your_key_here"
      }
    }
  }
}

Cursor

Add to your Cursor MCP config:

config.json

{
  "flexorch": {
    "command": "flexorch-mcp",
    "env": {
      "FLEXORCH_API_KEY": "dfx_your_key_here"
    }
  }
}

OpenAI Codex

Add to ~/.codex/config.toml:

toml

[mcp_servers.flexorch]
command = "uvx"
args = ["flexorch-mcp"]

[mcp_servers.flexorch.env]
FLEXORCH_API_KEY = "dfx_your_key_here"

Get your API key from app.flexorch.com/settings.

Verify connection

bash

flexorch-mcp --check
# → FlexOrch API key: dfx_xxx*** ✓
# → Connection: OK (api.flexorch.com)
# → Plan: Starter (1,200 credits/mo)
# → Tools: 9 registered

Example agent workflow

server.ts

User: "Process this invoice and export it as JSONL for fine-tuning."

Agent:
  1. document.process(file_url="https://...")   → job_id: 1234
  2. job.status(1234)                           → completed, execution_id: 567
  3. job.result(567)                            → vendor, total, date, PII masked
  4. dataset.build(execution_id=567)            → job_id: 1235
  5. job.status(1235)                           → completed, dataset_id: 89
  6. dataset.export(89, format="jsonl")         → inline JSONL content

Plan limits

All FlexOrch plan limits apply to MCP tool calls. Credits are consumed per document processed.

Plan	Credits/mo	Semantic search
Trial	1,200 (30 days)	—
Starter	1,200	—
Pro	6,000	✓
Enterprise	Custom	✓

Security

API key is read from the FLEXORCH_API_KEY environment variable — never passed as a tool argument
No data is stored or cached by this server — stateless proxy
PII masking is applied by FlexOrch's pipeline before results are returned
All communication with api.flexorch.com uses HTTPS

flexorch-audit — Standalone PII detection and document quality scoring (no account required)
flexorch-sdk — Python SDK for developers
flexorch-sdk-js — TypeScript SDK for developers
docs.flexorch.com — Full documentation

License

MIT — see LICENSE.

Flexorch MCP README