get_recent_commits_with_jobs_resource
AI agents call get_recent_commits_with_jobs_resource to retrieve information from PyTorch HUD MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The tool appears to fetch historical commit and job data from CI/CD systems without modifying, executing, or deleting anything. The 'get_' prefix and the pattern of sibling read-only tools support classification as Read. Confidence is moderate (0.75) rather than high because the description is empty, leaving some ambiguity about exact functionality.
From the tool's definition Tool name 'get_recent_commits_with_jobs_resource' indicates a retrieval operation ('get') that queries CI/CD analytics data for commits and associated jobs.
Attacks that exploit this kind of access
get_recent_commits_with_jobs_resource. It is categorised as a Read tool in the PyTorch HUD MCP Server MCP Server, which means it retrieves data without modifying state.
Register the PyTorch HUD MCP Server MCP server in PolicyLayer and add a rule for get_recent_commits_with_jobs_resource: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches PyTorch HUD MCP Server. Nothing to install.
get_recent_commits_with_jobs_resource is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the get_recent_commits_with_jobs_resource rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for get_recent_commits_with_jobs_resource. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
get_recent_commits_with_jobs_resource is provided by the PyTorch HUD MCP Server MCP server (izaitsevfb/claude-pytorch-treehugger). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
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