AI agents use unfavorite_tweet to create or update resources in X (Twitter) MCP server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your X (Twitter) MCP server environment.
Unfavoriting a tweet removes a previously set favorite/like. This is a reversible write operation (the user can re-favorite at any time). It modifies social interaction state but causes no irreversible data loss, financial impact, or code execution. Severity is low as the blast radius of accidentally unfavoriting tweets is minimal.
From the tool's definition 'Unfavorites a tweet' — removes a like/favorite from a tweet, which is a reversible modification of user interaction data
Documented attack patterns abuse exactly the kind of access unfavorite_tweet gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and X (Twitter) MCP server, and nothing reaches the server without passing your rules. This is the rule we recommend for unfavorite_tweet:
{
"version": "1",
"default": "deny",
"tools": {
"unfavorite_tweet": {
"limits": [
{
"counter": "unfavorite_tweet_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}unfavorite_tweet 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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Unfavorites a tweet. It is categorised as a Write tool in the X (Twitter) MCP server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the X (Twitter) MCP server MCP server in PolicyLayer and add a rule for unfavorite_tweet: 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 X (Twitter) MCP server. Nothing to install.
unfavorite_tweet 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 unfavorite_tweet 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 unfavorite_tweet. 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.
unfavorite_tweet is provided by the X (Twitter) MCP server MCP server (rafaljanicki/x-twitter-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 24 X (Twitter) MCP server tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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24 X (Twitter) MCP server tools catalogued and risk-classified — across an index of 42,500+ MCP servers.