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Start, stop, and monitor long-running command-line processes in the background.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Background Process MCP" yet — see the docs or source repo.
Start `npm run dev` in the project directory as a background process and keep monitoring its status; if it fails, return the error logs.
Confirmation that the process started, its current status, and a log summary if it fails.
Run `python batch_job.py` in the background, report status periodically, and tell me the exit code and key logs when it finishes.
Status updates while the job runs, plus the exit code and key output after completion.
Find the related command processes running in the background, stop the one using excessive resources, and tell me the result.
Identification of the stopped process, the stop action result, and its current status.
Start, stop, and monitor background shell processes without blocking chat.
Interact with Linux systems via MCP for monitoring, diagnostics, and operations.
Control agent workflows with stateful primitives and persisted execution facts.
Offload non-critical LLM tasks to your own model and save premium quota.
Chat with AI to retrieve documents and trigger MCP-powered tools.
Use one MCP server for filesystem, database, web, and system operations.