FlexOrch

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npx agentmarket install connector/dev-flexorch-flexorch-mcp

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What this server can do and what it asks for, from its tool list and install config. Checked Oct 25, 2026.

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Python package

Tools (9)

Read from the source code; the running server may differ. Descriptions are the server’s own words; hidden characters are shown as [U+…].

• dataset.buildBuild Dataset

  Package extracted records into a dataset for export (Step 4). Triggers an async dataset build from a completed execution. Returns a job_id immediately — poll with job.status until status='completed'. The completed response includes dataset_id, which you pass to dataset.export to retrieve all records as text. This step is required before calling dataset.export. Args: execution_id: Execution ID from a completed data_process job (from job.status or job.result). name: Dataset name. Auto-generated from the source filename if omitted. description: Optional description…

• dataset.chunksList RAG Chunksread-only

  Retrieve LangChain/LlamaIndex-ready text chunks from an indexed dataset (Pro+ plan). Returns paginated RAG chunks. Each chunk includes text, token count, and metadata (quality grade, PII masking status, document type, language). Use FlexOrchRetriever or FlexOrchReader from the flexorch-sdk for automatic pagination. The dataset must be indexed first via dataset.index(dataset_id). Args: dataset_id: ID of the indexed dataset. min_quality: Minimum quality grade to include: A, B, C, or D. Default: B. Chunks with grade at or above this threshold are returned. …

• dataset.exportExport Datasetread-only

  Download all records from a built dataset as text (Step 5 — final step). Returns the complete dataset content as a UTF-8 string directly in the response — no file download or separate URL needed. Call get_job_status after build_dataset and wait for status='completed' before calling this tool. Use the dataset_id from that completed response. Format guide: jsonl = LLM fine-tuning, rag = LangChain/LlamaIndex chunks, csv = spreadsheets, md = human-readable, xml = structured interchange. Binary formats (parquet, hf) cannot be returned via MCP — export them from the FlexOrch dashboard directly. A…

• dataset.indexIndex Dataset for RAG

  Trigger semantic indexing for a dataset — required before using dataset.chunks (Pro+ plan). Starts an async indexing job that splits the dataset into RAG-ready text chunks, generates embeddings, and stores them for semantic search. Indexing is idempotent: calling it again on an already-indexed dataset re-indexes with fresh embeddings. Indexing typically completes in 10–60 seconds depending on dataset size. After indexing, use dataset.chunks(dataset_id) to retrieve the text chunks. Args: dataset_id: ID of the built dataset to index (from job.status after dataset.build).

• dataset.searchSearch Documentsread-only

  Search across all indexed FlexOrch datasets by keyword or meaning. Use this to find specific documents or records without processing a new file. Requires at least one dataset to exist. Structured search works on all plans. Semantic and hybrid modes require a Pro plan — a clear upgrade message is returned if the plan is insufficient. mode='auto' picks structured on free plans, hybrid on Pro+. Args: query: Search query — natural language or keyword. Max 1000 characters. top_k: Number of results to return. Default: 5, max: 50. mode: Search strategy — auto (default), structured, sema…

• document.processProcess Document

  Submit a document for processing — this is always the first step (Step 1 of 5). Downloads the file from file_url, then submits it to FlexOrch for automatic classification, structured field extraction, PII detection/masking, and quality scoring. Processing is asynchronous — this tool returns immediately with a job_id. You MUST call job.status(job_id) every 3–5 seconds until status='completed' before calling job.result. Args: file_url: Publicly accessible URL of the document (http/https only, max 50 MB). Supported: PDF, DOCX, TXT, XLSX, HTML, XML, EML, JPG, PNG, TIFF. mas…

• document.reprocessReprocess Document

  Re-queue an already-uploaded document through the pipeline. Use this to re-run extraction/PII detection/quality scoring on a document you've already processed — e.g. after a document_type_hint change, without downloading and re-uploading the original file. Returns immediately with a job_id — poll with job.status the same way as after document.process. Only works for documents whose original file is still stored on the server (locally uploaded, not connector-sourced). If the file is no longer available, re-upload it with document.process instead. Args: document_id: ID of a previously pro…

• job.resultGet Extraction Resultread-only

  Read structured fields extracted from a completed document (Step 3). Use the execution_id from a completed data_process job (job.status response). Returns document type, detected language, quality grade (A–D), PII summary, column list, and extracted field values. If no dataset has been built yet, the response includes a fields_hint guiding you to call dataset.build next. To retrieve all rows as a file, proceed to dataset.build → dataset.export. Note: Masked fields appear as [MASKED_TYPE] placeholders — raw PII is never returned. Note: execution_id comes from data_process jobs only; dataset_b…

• job.statusGet Job Statusread-only

  Poll a job until it finishes — call this after document.process or dataset.build (Step 2). Call repeatedly every 3–5 seconds until status is 'completed' or 'failed'. For data_process jobs: the completed response includes execution_id — pass it to job.result. For dataset_build jobs: the completed response includes dataset_id — pass it to dataset.export. Args: job_id: Job ID returned by document.process or dataset.build.

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Last commit

Sep 20, 2026 (1 month ago)

Last release

Aug 6, 2026 (2 months ago)

Last package publish

Sep 19, 2026 (1 month ago)

From GitHub (fetched Oct 24, 2026) and the package registry.

Details

Registry name

io.github.dev-flexorch/flexorch-mcp

Version

0.1.2

Auth

API key

Packages

pypi flexorch-mcp

License

MIT

Repository

github.com/flexorch/flexorch-mcp

First seen

Oct 24, 2026

Last checked

Oct 25, 2026

Source

Official MCP Registrygithub-graphql