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Let MCP-aware agents use Modal serverless compute, GPUs, and headless browsing.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "pi-modal-mcp" yet — see the docs or source repo.
Use pi-modal-mcp to start a GPU worker on Modal, run this machine learning inference task, and return the run status plus a result summary.
Returns the job status, a summary of the GPU run, and relevant output details.
Use pi-modal-mcp to open the target webpage, wait until it finishes loading, capture a screenshot of the homepage, and summarize the key information on the page.
Returns a webpage screenshot and a brief summary of the page content.
First use pi-modal-mcp to visit a specified webpage and collect page content, then send the extracted data to a compute task on Modal for processing, and finally summarize the results.
Returns the web collection results, compute task output, and a consolidated final conclusion.
Developers or researchers can let an MCP-aware agent send compute jobs to Modal instead of relying only on a local environment. It is useful for automated workflows that need serverless compute resources.
When a task requires GPU workers, this tool acts as a bridge between the agent and Modal. It fits agent workflows that need model inference or other GPU-backed workloads.
In scenarios that need web access, an agent can use it to drive headless Chromium for page browsing and screenshots. It is suitable for collecting webpage content or recording how a page renders.
It enables MCP-aware agents to use Modal serverless compute, including GPU workers and headless Chromium for web browsing with screenshots.
Based on the provided description, it supports three core capabilities: driving Modal serverless compute, running GPU workers, and browsing webpages with headless Chromium plus screenshots.
The provided material does not include installation steps, runtime requirements, or key configuration details. For exact prerequisites, see the source repository.
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