Export all feeds as OPML XML string.
AI agents call export_opml_tool to retrieve information from MCP Feed Reader without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool reads feed data from the SQLite backend and serializes it into an OPML XML format. It only retrieves and formats existing data without modifying, deleting, or executing anything. The blast radius is minimal — at worst it exposes the list of subscribed feeds.
From the tool's definition Export all feeds as OPML XML string
Attacks that exploit this kind of access
Export all feeds as OPML XML string. It is categorised as a Read tool in the MCP Feed Reader MCP Server, which means it retrieves data without modifying state.
Register the MCP Feed Reader MCP server in PolicyLayer and add a rule for export_opml_tool: 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 Feed Reader. Nothing to install.
export_opml_tool 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 export_opml_tool 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 export_opml_tool. 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.
export_opml_tool is provided by the MCP Feed Reader MCP server (pypi:mcp-feed-reader-crunchtools). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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