Server data from the Official MCP Registry
Classify documents, extract structured fields, mask PII, export JSONL/RAG datasets for AI agents.
Classify documents, extract structured fields, mask PII, export JSONL/RAG datasets for AI agents.
flexorch-mcp is a well-structured MCP server that safely proxies FlexOrch's document processing API. Authentication via environment variable is properly implemented, permissions are appropriate for the stated purpose (network calls to a managed API), and code quality is high with strong input validation and error handling. Minor code quality observations exist but do not affect security posture. Supply chain analysis found 3 known vulnerabilities in dependencies (0 critical, 3 high severity). Package verification found 1 issue.
7 files analyzed · 8 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
This plugin requests these system permissions. Most are normal for its category.
Set these up before or after installing:
Environment variable: FLEXORCH_API_KEY
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-dev-flexorch-flexorch-mcp": {
"env": {
"FLEXORCH_API_KEY": "your-flexorch-api-key-here"
},
"args": [
"flexorch-mcp"
],
"command": "uvx"
}
}
}From the project's GitHub README.
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.
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.
| Tool | Description |
|---|---|
process_document | Upload and process a document (PDF, DOCX, TXT, XLSX, HTML, XML, EML, JPG, PNG, TIFF) |
get_job_status | Poll a processing job until completed or failed |
get_extraction_result | Get structured extracted fields from a completed job |
build_dataset | Build a structured dataset from a completed execution |
search_documents | Semantic search across indexed datasets (Pro+) |
export_dataset | Export a dataset as JSONL, CSV, JSON, XML, MD, or RAG (LangChain/LlamaIndex chunks) |
pip install flexorch-mcp
Requires Python 3.10+.
Add to ~/.claude/claude_desktop_config.json:
{
"mcpServers": {
"flexorch": {
"command": "flexorch-mcp",
"env": {
"FLEXORCH_API_KEY": "dfx_your_key_here"
}
}
}
}
Add to your Cursor MCP config:
{
"flexorch": {
"command": "flexorch-mcp",
"env": {
"FLEXORCH_API_KEY": "dfx_your_key_here"
}
}
}
Get your API key from app.flexorch.com/settings.
flexorch-mcp --check
# → FlexOrch API key: dfx_xxx*** ✓
# → Connection: OK (api.flexorch.com)
# → Plan: Starter (1,200 credits/mo)
# → Tools: 6 registered
User: "Process this invoice and export it as JSONL for fine-tuning."
Agent:
1. process_document(file_url="https://...") → job_id: 1234
2. get_job_status(1234) → completed, execution_id: 567
3. get_extraction_result(567) → vendor, total, date, PII masked
4. build_dataset(execution_id=567) → job_id: 1235
5. get_job_status(1235) → completed, dataset_id: 89
6. export_dataset(89, format="jsonl") → inline JSONL content
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 | ✓ |
FLEXORCH_API_KEY environment variable — never passed as a tool argumentapi.flexorch.com uses HTTPSMIT — see LICENSE.
Be the first to review this server!
by Modelcontextprotocol · Developer Tools
Read, search, and manipulate Git repositories programmatically
by Modelcontextprotocol · Developer Tools
Web content fetching and conversion for efficient LLM usage
by Toleno · Developer Tools
Toleno Network MCP Server — Manage your Toleno mining account with Claude AI using natural language.