Content
# flexorch-mcp
<!-- mcp-name: io.github.dev-flexorch/flexorch-mcp -->
[](https://smithery.ai/servers/developer-ty82/flexorch-mcp)
[](https://pypi.org/project/flexorch-mcp/)
[](https://github.com/flexorch/flexorch-mcp/actions/workflows/ci.yml)
[](https://opensource.org/licenses/MIT)
[](https://www.python.org/downloads/)
**MCP server for FlexOrch — SDK for machines.**
Connect Claude and other MCP-compatible agents to the [FlexOrch](https://flexorch.com) 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](https://github.com/flexorch/flexorch-sdk) (Python) or [flexorch-sdk-js](https://github.com/flexorch/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) |
| `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) |
---
## Installation
```bash
pip install flexorch-mcp
```
Requires Python 3.10+.
---
## Configuration
### Claude Desktop
Add to `~/.claude/claude_desktop_config.json`:
```json
{
"mcpServers": {
"flexorch": {
"command": "flexorch-mcp",
"env": {
"FLEXORCH_API_KEY": "dfx_your_key_here"
}
}
}
}
```
### Cursor
Add to your Cursor MCP 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](https://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: 6 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.
| 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
---
## Related
- [flexorch-audit](https://github.com/flexorch/flexorch-audit) — Standalone PII detection and document quality scoring (no account required)
- [flexorch-sdk](https://github.com/flexorch/flexorch-sdk) — Python SDK for developers
- [flexorch-sdk-js](https://github.com/flexorch/flexorch-sdk-js) — TypeScript SDK for developers
- [docs.flexorch.com](https://docs.flexorch.com) — Full documentation
---
## License
MIT — see [LICENSE](LICENSE).
