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306,585 tools. Last updated 2026-07-25 15:54

"Local small language model for filesystem and network tasks" matching MCP tools:

  • Exports the AI Context file for a given master, combining network state and CLI commands for language model planning.
    Apache 2.0
  • List workspaces visible through cloud RLS, returning workspace IDs for remote tools without exposing local filesystem paths.
    MIT
  • Upload local files to Google Cloud Run by specifying absolute file paths. Enables deployment of local filesystem assets to a specified Cloud Run service in the user's Google Cloud project.
    Apache 2.0
  • Load a saved sktime model from a local directory to restore it for reuse in time series forecasting or analysis tasks.
    BSD 3-Clause
  • Download files or folders from Proton Drive to your local filesystem. Supports recursive folder downloads and overwrites existing files.
    MIT
  • Save a cached attachment to the MCP server's filesystem using its cache key. Specify the full server path to store files for server-side processing or shared network access.
    MIT

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  • Check if a task runs locally vs cloud. Save money on calls that don't need cloud inference.

  • Zoom Tasks server for creating, updating, assigning, and synchronizing task workflows.

  • Download Minecraft server instance files from MCSManager to the local filesystem for backup, analysis, or modification. Specify the remote file path and optional local output location.
    MIT
  • Check installed Whisper models with details on size, active status, quantization, and recommended use. No network required.
    Sleepycat
  • Scan any local filesystem path for leaked secrets like API keys and passwords. Detects exposures without sending data externally and returns redacted findings.
    GPL 3.0
  • Retrieve a language and size breakdown for a local repository, providing total files, total lines, and per-extension details sorted by line count.
    MIT
  • Retrieve available model IDs from the local Grok model cache for selection in tasks.
    MIT
  • Generate new code from natural-language instructions using a local Ollama model. Optionally provide a context file to guide style and API usage.
    MIT
  • Get local system hardware details: CPU model, RAM, disk space, uptime, and network interfaces with IPs and MACs, directly from your machine.
    MIT
  • Delegate all language model tasks—reasoning, text generation, coding, analysis, and more—to a local LLM. Pass the full task as prompt and optionally set a system instruction.
    MIT
  • Download files from MEGA cloud to your local filesystem using the remote path and optional local destination.
    MIT
  • Count tokens in a conversation locally using cl100k_base encoding. Returns total, model, encoding, and per-message breakdown without network calls.
    MIT