Add many packages to pyproject.toml at once and update the virtual environment.
AI agents use add_packages to create or update resources in Venv — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Venv environment.
This tool creates or modifies data (pyproject.toml entries and venv dependencies) in a reversible manner. While it alters the development environment, the changes can be undone by removing packages or restoring the previous configuration. It does not execute arbitrary code, delete irreversibly, or move money.
From the tool's definition Tool description explicitly states 'Add many packages to pyproject.toml' and 'update the virtual environment' — modifying configuration files and environment state.
Documented attack patterns abuse exactly the kind of access add_packages gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Venv, and nothing reaches the server without passing your rules. This is the rule we recommend for add_packages:
{
"version": "1",
"default": "deny",
"tools": {
"add_packages": {
"limits": [
{
"counter": "add_packages_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}add_packages stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
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Add many packages to pyproject.toml at once and update the virtual environment. It is categorised as a Write tool in the Venv MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Venv MCP server in PolicyLayer and add a rule for add_packages: 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 Venv. Nothing to install.
add_packages is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the add_packages 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 add_packages. 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.
add_packages is provided by the Venv MCP server (sparfenyuk/venv-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Venv, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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6 Venv tools catalogued and risk-classified — across an index of 43,000+ MCP servers.