AI agents use like_tweet to create or update resources in X(Twitter) V2 MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your X(Twitter) V2 MCP Server environment.
Liking a tweet is a reversible write operation (it can be unliked). The description is empty, so confidence is reduced, but the name 'like_tweet' on a Twitter API server leaves little ambiguity. Misuse could result in unwanted social interactions but has limited blast radius.
From the tool's definition Tool name 'like_tweet' on a Twitter/X API server; description is empty but name strongly implies liking/favoriting a tweet, which is a reversible write action.
Documented attack patterns abuse exactly the kind of access like_tweet gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and X(Twitter) V2 MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for like_tweet:
{
"version": "1",
"default": "deny",
"tools": {
"like_tweet": {
"limits": [
{
"counter": "like_tweet_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}like_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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like_tweet. It is categorised as a Write tool in the X(Twitter) V2 MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the X(Twitter) V2 MCP Server MCP server in PolicyLayer and add a rule for like_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) V2 MCP Server. Nothing to install.
like_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 like_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 like_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.
like_tweet is provided by the X(Twitter) V2 MCP Server MCP server (nexusx-mcp/x-v2-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from X(Twitter) V2 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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16 X(Twitter) V2 MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.