flexorch-mcp

Convert unstructured business documents (PDF, DOCX, invoices, contracts, payroll sheets) into structured, LLM-ready datasets with automatic classification, field extraction, PII masking, and quality scoring. **6 async tools:** - `process_document` — submit document for processing - `get_job_status` — poll until complete - `get_extraction_result` — read structured fields + quality grade - `build_dataset` — package records into a named dataset - `export_dataset` — download as JSONL, RAG, CSV, or Markdown - `search_documents` — keyword + semantic search across datasets **Requires:** FlexOrch API key — get one at [app.flexorch.com/settings](https://app.flexorch.com/settings)

该来源不提供完整文件导出（国内平台多为平台内托管），仅存元数据与原链

接入信息

传输形态: http
鉴权方式: 需 API Key（需要配置：apiKey）
端点: https://flexorch-mcp--developer-ty82.run.tools

该服务需要凭证，请按官方文档申请后替换占位符

{
  "mcpServers": {
    "flexorch-mcp": {
      "headers": {
        "Authorization": "Bearer \u003cYOUR_KEY\u003e"
      },
      "url": "https://flexorch-mcp--developer-ty82.run.tools"
    }
  }
}

能力清单

工具	说明
document.process	Submit a document for processing — Step 1 of 5. Returns job_id immediately; poll job.status until completed.
job.status	Poll a job until it finishes — Step 2. Call every 3-5s until status is completed or failed.
job.result	Read structured fields extracted from a completed document — Step 3.
dataset.build	Package extracted records into a dataset for export — Step 4. Returns job_id; poll job.status until completed.
dataset.search	Search across all indexed FlexOrch datasets by keyword or semantic meaning.
dataset.export	Download all records from a built dataset as text — Step 5, final step.
dataset.index	Trigger semantic indexing for a dataset (Pro+ plan required). Must be called before dataset.chunks. Indexing is idempotent and typically completes in 10–60 seconds.
dataset.chunks	Retrieve LangChain/LlamaIndex-ready text chunks from an indexed dataset (Pro+ plan required). Dataset must be indexed first via dataset.index.

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