Install a Wasmer registry package into an isolated sandbox and receive the exact commands it provides, letting you add missing tools beyond the default Python environment.
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580,509 tools. Updated 2026-09-16 13:56
"Wasmer" matching MCP tools:
- Lists all LG ThinQ devices on your account to find the washer's deviceId for other tools.MIT
- Send start, stop, power-off, or wake commands to an LG washer, specifying device and location for location-scoped models. Verify profile first for supported operations.MIT
- Retrieve a washer's capability profile with exact controllable properties and allowed values for the specific model. Consult before controlling to avoid invalid command errors.MIT
- Retrieve the washer's live status to see if it is running, the current cycle, and remaining time.MIT
- Retrieve the full JSON details of a specific code review by providing its review ID.MIT
Matching MCP Servers
- FlicenseAqualityBmaintenanceEnables running Python and commands inside isolated, persistent Wasmer sandboxes on the host, while also exposing an Edge-deployed Postgres-backed service for storing notes and collecting feedback.8-
- FlicenseNot gradedqualityDmaintenanceA demonstration MCP server built with FastMCP that provides basic tools (addition calculator), dynamic resources (personalized greetings), and prompt templates, designed to run on Wasmer Edge.-
- List tasks from the review system with optional status filtering and item limit. Retrieve pending, in_progress, completed, or cancelled tasks.MIT
- Initiates task execution, sets status to in_progress, and provides an execution guide. Start tasks with clear, step-by-step instructions.MIT
- Convert code review findings into actionable tasks automatically. Transform review results into task items to manage follow-up work efficiently.MIT
- Send arbitrary JSON control commands to the washer for model-specific settings like timers and remote toggles when higher-level tools lack coverage.MIT
- Combines review rules and git diff to generate a Korean review prompt package for LLMs. Automatically converts 'main' base to 'origin/main'.MIT
- Manually create a new task to record code review results, capturing title, description, file path, line range, category, severity, and optional patch diff. Enables manual entry of review findings for management.MIT
- Shows the environment variables and paths the server currently recognizes, enabling quick verification of configuration settings.MIT
- Retrieves overall task statistics to track code review progress and manage task workloads effectively.MIT
- Convert a review ID to Markdown and save it as a file. Use it to extract and store specific code review results in a portable format.MIT
- Save code review results as JSON and get a unique review ID for tracking and later retrieval. Accepts structured findings, criteria feedback, and risk levels.MIT
- Retrieve detailed information for a specific task by its ID, including code review results and status.MIT
- Verify task completion by reviewing provided changes and information, confirming all work is done.MIT
- Mark a task as complete by supplying its ID and an optional note describing the verification or fix.MIT
- Update a task's status to pending, in_progress, completed, or cancelled using its ID. Streamline review workflow by tracking task progress.MIT
- Collects git diff between base and head branches, automatically treating 'main' as 'origin/main', to extract code changes for review.MIT