create_context_cache
AI agents use create_context_cache to create or update resources in Gpal — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Gpal environment.
The tool creates a new context cache resource, which is a reversible write operation. While the description is empty (lowering confidence), the name and server context (autonomous codebase analysis tools) suggest it stores or caches analysis state. This is Write rather than Read (it modifies state) or Destructive (caches can be cleared).
From the tool's definition Tool name 'create_context_cache' indicates creation of a cache artifact. Server context shows this tool is part of a Gemini integration system with codebase exploration capabilities. The 'create' prefix aligns with Write category (data creation).
Documented attack patterns abuse exactly the kind of access create_context_cache gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Gpal, and nothing reaches the server without passing your rules. This is the rule we recommend for create_context_cache:
{
"version": "1",
"default": "deny",
"tools": {
"create_context_cache": {
"limits": [
{
"counter": "create_context_cache_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}create_context_cache 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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create_context_cache. It is categorised as a Write tool in the Gpal MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Gpal MCP server in PolicyLayer and add a rule for create_context_cache: 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 Gpal. Nothing to install.
create_context_cache 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 create_context_cache 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 create_context_cache. 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.
create_context_cache is provided by the Gpal MCP server (tobert/gpal). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Gpal, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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19 Gpal tools catalogued and risk-classified — across an index of 43,000+ MCP servers.