AI agents use add_bookmark to create or update resources in Raindrop Io MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Raindrop Io MCP Server environment.
This tool creates new bookmark records, which is a reversible write operation. The empty description provides no additional context, but the tool name and server context clearly indicate data creation. Severity is medium because misuse could create unwanted bookmarks or clutter the user's bookmark collection, but the effect is reversible (bookmarks can be deleted).
From the tool's definition Tool name 'add_bookmark' and server description stating the tool 'add, search, and organize bookmarks'. The action of adding a bookmark creates or modifies bookmark data in Raindrop.io.
Documented attack patterns abuse exactly the kind of access add_bookmark gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Raindrop Io MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for add_bookmark:
{
"version": "1",
"default": "deny",
"tools": {
"add_bookmark": {
"limits": [
{
"counter": "add_bookmark_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}add_bookmark 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_bookmark. It is categorised as a Write tool in the Raindrop Io MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Raindrop Io MCP Server MCP server in PolicyLayer and add a rule for add_bookmark: 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 Raindrop Io MCP Server. Nothing to install.
add_bookmark 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_bookmark 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_bookmark. 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_bookmark is provided by the Raindrop Io MCP Server MCP server (sachin-philip/raindrop.io-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Raindrop Io MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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4 Raindrop Io MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.