pf_feed

THE RISK

Low Risk

Why pf_feed needs a policy

This tool retrieves timeline data from a federated social platform without creating, modifying, deleting, or executing operations. It is a straightforward query operation that returns existing data. The rate limiting (60/hour) further confirms it is a passive read operation. Misuse would have minimal blast radius—an attacker could only retrieve accessible timeline information without causing side effects.

From the tool's definition Tool name 'pf_feed' and description 'Fetch a timeline' with options for home, public, local, and notifications indicates data retrieval with no modification or execution. The verb 'Fetch' and rate-limiting disclosure are typical of read-only API endpoints.

Documented attack patterns abuse exactly the kind of access pf_feed gives an agent:

POLICY

How to control pf_feed

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 pf_feed:

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "pf_feed": {}
  }
}

pf_feed is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.

Create a free account and register Crow — nothing to install.
Add this policy — paste it, or build it visually.
Point your MCP client (Claude, Cursor, anything) at your gateway URL.

CAP THIS TOOL →

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EXPLORE

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Go deeper

The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Data exfiltration → How read access becomes an exfiltration channel when chained with untrusted content.
MCP token cost → What connecting this server costs in context-window tokens on every request.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →

FAQ

Questions about pf_feed

What does the pf_feed tool do? +

Fetch a timeline. home = follows; public = local+federated; local = this instance; notifications = mentions/likes/follows. Rate-limited: 60/hour. It is categorised as a Read tool in the Crow MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on pf_feed? +

Register the Crow MCP server in PolicyLayer and add a rule for pf_feed: 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.

What risk level is pf_feed? +

pf_feed is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit pf_feed? +

Yes. Add a rate_limit block to the pf_feed 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.

How do I block pf_feed completely? +

Set action: deny in the PolicyLayer policy for pf_feed. 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.

What MCP server provides pf_feed? +

pf_feed 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.

Enforce policy on every Crow tool call.

Start from Crow, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

CHECK YOUR STACK →