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134,903 tools. Last updated 2026-05-14 11:19

"Automating Workflow for File Processing and Communication" matching MCP tools:

  • Parse a workflow YAML file and retrieve its complete structure for inspection or further processing.
    Apache 2.0
  • Queues a log export job for processing after creation. Use get_log_export to track progress and download_log_export to retrieve results once completed.
    MIT
  • Upload a BOM file from your local filesystem to initiate part matching and obtain a job ID for processing status tracking.
    Apache 2.0
  • List documents in a Needle collection to check processing status, inventory available files, and verify document availability before searching.
    MIT
  • Check BOM processing status and identify unknown or unmatched parts. Unknown components are highlighted for attention after processing completes.
    Apache 2.0

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  • Create, browse, remix, collaborate on, and run durable AI workflow nodes from MCP hosts.

  • Image processing for AI agents. Resize, convert, compress, and pipeline images.

  • Retrieve detailed information about a media file, including type, dimensions, size, upload status, and aspect ratio. Check if the file has finished processing before attaching to a post.
    MIT
  • Discover pre-built workflow skills for common tasks like invoice processing and content pipelines. Filter by category to find reusable patterns with usage examples and context reduction metrics.
    MIT
  • Build a complete symbol index for the current project by performing full re-indexing and loading it into memory using parallel processing.
    MIT
  • Publishes a video to your Instagram feed, waiting for processing to complete before sharing.
    MIT
  • Retrieve the full communication history for a contact by providing their contact ID, including calls, emails, and messages.
    MIT
  • Display file contents by concatenating them for viewing or processing within the Shell-MCP server's secure execution environment.
    MIT
  • List recent workflow runs for debugging and reference, enabling efficient AI workflow orchestration by chaining multi-step LLM operations.
    MIT
  • Send input to a running process and automatically receive the response. Essential for local file analysis (CSV, JSON, data processing) using REPLs like Python, avoiding tools that cannot access files.
  • Start a new terminal process for local file analysis and command execution. Uses intelligent state detection to manage REPLs, scripts, and system commands. Ideal for CSV, JSON, log processing, and system operations.
  • Create named lists of files, URLs, or items for parallel processing operations across multiple elements in a single workflow.
    Apache 2.0
  • Start a durable workflow execution. Pass the workflow ID and input data to begin processing immediately.
  • Approve a workflow awaiting human confirmation to resume execution. Provide the workflow ID and approver name for audit trail.
    MIT