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FlexOrch

Official registry Data and databases

Classify documents, extract structured fields, mask PII, export JSONL/RAG datasets for AI agents.

Source code Documentation

Install

Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).

PYPI package flexorch-mcp
Claude Code 
claude mcp add flexorch -e 'FLEXORCH_API_KEY=<your flexorch_api_key>' -- uvx flexorch-mcp==0.1.2
JSON configuration (Claude Desktop, Cursor, VS Code) 
{
    "mcpServers": {
        "flexorch": {
            "command": "uvx",
            "args": [
                "flexorch-mcp==0.1.2"
            ],
            "env": {
                "FLEXORCH_API_KEY": "<your flexorch_api_key>"
            }
        }
    }
}

Environment variables

  • FLEXORCH_API_KEY required secret FlexOrch API key — get one at app.flexorch.com/settings

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  1. flexorch-mcp
  2. What this is
  3. Tools
  4. Installation
  5. Configuration
  6. Verify connection
  7. Example agent workflow
  8. Plan limits
  9. Security
  10. Related
  11. License

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

ToolDescription
document.processUpload and process a document (PDF, DOCX, TXT, XLSX, HTML, XML, EML, JPG, PNG, TIFF)
document.reprocessRe-queue an already-uploaded document through the pipeline
job.statusPoll a processing job until completed or failed
job.resultGet structured extracted fields from a completed job
dataset.buildBuild a structured dataset from a completed execution
dataset.searchSemantic search across indexed datasets (Pro+)
dataset.exportExport a dataset as JSONL, CSV, JSON, XML, MD, or RAG (LangChain/LlamaIndex chunks)
dataset.indexTrigger semantic vector indexing for a dataset (Pro+)
dataset.chunksRetrieve paginated RAG-ready text chunks from an indexed dataset (Pro+)

Installation

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

Add to your Cursor MCP config:

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

Add to ~/.codex/config.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

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

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.

PlanCredits/moSemantic search
Trial1,200 (30 days)—
Starter1,200—
Pro6,000✓
EnterpriseCustom✓

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

License

MIT — see LICENSE.

Frequently asked questions

What is FlexOrch?

Classify documents, extract structured fields, mask PII, export JSONL/RAG datasets for AI agents.

How do I install FlexOrch?

It runs on your machine. In Claude Code: claude mcp add flexorch -e 'FLEXORCH_API_KEY=<your flexorch_api_key>' -- uvx flexorch-mcp==0.1.2. For other clients, paste the JSON configuration from this page into their MCP settings.

Does FlexOrch need an API key?

Yes. It expects FLEXORCH_API_KEY, which you set in its configuration.

Is FlexOrch open source?

Yes. Its code is on GitHub under the MIT license.

Who maintains FlexOrch?

It is published by flexorch. AI.tn lists it but does not maintain or endorse it.

From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.