Find all dependencies (imports/requires) for a file or symbol. Useful for understanding what code needs.
AI agents call get_dependencies to retrieve information from MCP Context Manager without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries and retrieves dependency information from code, returning metadata about imports and requirements. It has no side effects, does not execute code, does not modify data, and does not delete anything. It is a pure read operation used for code analysis and navigation.
From the tool's definition Tool name 'get_dependencies' and description 'Find all dependencies (imports/requires) for a file or symbol' indicate data retrieval only. No modification, deletion, execution, or financial operations are performed.
Documented attack patterns abuse exactly the kind of access get_dependencies gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and MCP Context Manager, and nothing reaches the server without passing your rules. This is the rule we recommend for get_dependencies:
{
"version": "1",
"default": "deny",
"tools": {
"get_dependencies": {}
}
}get_dependencies is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Find all dependencies (imports/requires) for a file or symbol. Useful for understanding what code needs. It is categorised as a Read tool in the MCP Context Manager MCP Server, which means it retrieves data without modifying state.
Register the MCP Context Manager MCP server in PolicyLayer and add a rule for get_dependencies: 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 MCP Context Manager. Nothing to install.
get_dependencies 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_dependencies 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_dependencies. 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_dependencies is provided by the MCP Context Manager MCP server (transparentlyok/mcp-context-manager). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from MCP Context Manager, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
21 MCP Context Manager tools catalogued and risk-classified — across an index of 43,000+ MCP servers.