flexorch-mcp

flexorch-mcp

<!-- mcp-name: io.github.dev-flexorch/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.

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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.

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Tools

| Tool | Description | |------|-------------| | document.process | Upload and process a document (PDF, DOCX, TXT, XLSX, HTML, XML, EML, JPG, PNG, TIFF) | | 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) |

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Installation

pip install flexorch-mcp

Requires Python 3.10+.

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Configuration

Claude Desktop

Add to ~/.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.

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Verify connection

flexorch-mcp --check
# → FlexOrch API key: dfx_xxx*** ✓
# → Connection: OK (api.flexorch.com)
# → Plan: Starter (1,200 credits/mo)
# → Tools: 6 registered

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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

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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 | ✓ |

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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

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Related

• 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

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License

MIT — see LICENSE.