Save a URL to Wallabag for reading later. Wallabag fetches and stores the article content.
AI agents use crow_wallabag_save to create or update resources in Crow — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Crow environment.
This tool creates new records (saved articles) in a Wallabag instance, which is a reversible write operation. It does not execute arbitrary code, delete data, or commit financial transactions. The medium severity reflects that bulk misuse could fill storage or spam a user's reading list, but the impact is bounded and reversible.
From the tool's definition 'Save a URL to Wallabag' and 'stores the article content' indicate creation and persistent storage of data. The tool modifies a reading list by adding new entries.
Documented attack patterns abuse exactly the kind of access crow_wallabag_save gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Crow, and nothing reaches the server without passing your rules. This is the rule we recommend for crow_wallabag_save:
{
"version": "1",
"default": "deny",
"tools": {
"crow_wallabag_save": {
"limits": [
{
"counter": "crow_wallabag_save_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
} crow_wallabag_save 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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Save a URL to Wallabag for reading later. Wallabag fetches and stores the article content. It is categorised as a Write tool in the Crow MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Crow MCP server in PolicyLayer and add a rule for crow_wallabag_save: 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 Crow. Nothing to install.
crow_wallabag_save 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 crow_wallabag_save 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 crow_wallabag_save. 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.
crow_wallabag_save is provided by the Crow MCP server (kh0pper/crow). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Crow, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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576 Crow tools catalogued and risk-classified — across an index of 43,000+ MCP servers.