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FlexOrch

Registre officiel Données et bases de données

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

Code source Documentation

Installation

Ajoutez ceci à la configuration MCP de votre client (Claude Desktop : claude_desktop_config.json ; Cursor : .cursor/mcp.json ; VS Code et les autres utilisent la même forme « mcpServers »).

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

Variables d'environnement

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

Documentation

Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.

Sommaire
  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.

Questions fréquentes

Qu'est-ce que FlexOrch ?

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

Comment installer FlexOrch ?

Il s'exécute sur votre machine. Dans Claude Code : claude mcp add flexorch -e 'FLEXORCH_API_KEY=<your flexorch_api_key>' -- uvx flexorch-mcp==0.1.2. Pour les autres clients, collez la configuration JSON de cette page dans leurs réglages MCP.

Faut-il une clé API pour FlexOrch ?

Oui. Il attend FLEXORCH_API_KEY, à renseigner dans sa configuration.

FlexOrch est-il open source ?

Oui. Son code est sur GitHub sous licence MIT.

Qui maintient FlexOrch ?

Il est publié par flexorch. AI.tn le référence sans le maintenir ni le recommander.

Issu du registre MCP officiel. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.