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FlexOrch MCP

FlexOrch MCP

Local
github.com/flexorchFiles & Storage1Updated 5w ago

About FlexOrch MCP

FlexOrch MCP is a stateless proxy that lets MCP-compatible agents use FlexOrch’s managed document-processing pipeline. It is intended for document workflows that classify files, extract structured fields, detect and mask PII, and build or export datasets; a FlexOrch account and API key are required.

Key features

  1. 01Process and reprocess documents
  2. 02Check job status and retrieve results
  3. 03Build structured datasets
  4. 04Export JSONL, CSV, and other formats
  5. 05Search and index datasets semantically
  6. 06Retrieve RAG-ready text chunks

Use cases

  1. 01Extract structured fields from invoices
  2. 02Mask PII before using document results
  3. 03Build datasets for LLM workflows
  4. 04Export indexed documents as RAG chunks

MCP support

The server exposes FlexOrch API operations as MCP tools and forwards processing to FlexOrch-managed infrastructure. It stores or caches no data and reads the API key from FLEXORCH_API_KEY.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"dev-flexorch-flexorch": {
"command": "uvx",
"args": [
"flexorch-mcp"
],
"env": {
"FLEXORCH_API_KEY": "<FLEXORCH_API_KEY>"
}
}
}
}
Run commanduvx flexorch-mcp
Environment variables to set
FLEXORCH_API_KEYSecretFlexOrch API key — get one at app.flexorch.com/settings

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
pypiflexorch-mcp0.1.2

Tools

6

Saved tool list · updated 2w ago

ParameterTypeRequiredDescription
file_urlstringYes
mask_piibooleanNo
document_typestringNo

Details

From the project README

flexorch-mcp

smithery badge PyPI version CI License: MIT Python 3.10+ flexorch-mcp MCP server Glama score

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

Related


License

MIT — see LICENSE.

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