AI agents use unfavorite_tweet to create or update resources in Twikit — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Twikit environment.
Unliking a tweet is a reversible write action (the user can re-like the tweet at any time). It modifies social interaction state but causes no irreversible data loss, financial impact, or code execution.
From the tool's definition Unlike a tweet by ID — removes a previously set favorite/like, which is a reversible modification to 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 Twikit, 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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Unlike a tweet by ID. It is categorised as a Write tool in the Twikit MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Twikit 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 Twikit. 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 Twikit MCP server (tangivis/twitter-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Twikit, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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59 Twikit tools catalogued and risk-classified — across an index of 43,000+ MCP servers.