X (Twitter) MCP. Analyze Public Sentiment and Engagement Metrics

X (Twitter) MCP Server - Analyze Social Data

Forget writing complex scrapers or wrestling with API key limits. This server gives your AI client direct, structured access to X's public data using the full capabilities of their API. You don't need a developer degree or hours spent in Postman; you just talk to your agent like normal and it handles the data retrieval.

Finding Specific Discussions

You can make your agent search for recent conversations across the platform. Just give it keywords, hashtags, or names—it pulls public tweets that match those criteria from within the last seven days. This is perfect when you're trying to monitor a specific topic or check out what people are saying about a competitor right now.

It handles searching using multiple filters simultaneously, so whether you want to track a general idea or zero in on a niche community, it finds the relevant tweets published recently.

Auditing Tweet Performance Metrics

When you've found a tweet that looks interesting, you don't just get the text. You provide your agent with the specific Tweet ID, and it pulls back all the hard numbers attached to that post. This means you instantly get the full content text alongside the exact counts for likes, retweets, and replies.

It’s not some estimate; it’s the raw data showing how widely that piece of content was spread and what kind of engagement it generated. You can analyze performance metrics on demand without running complex reporting tools.

Retrieving User Profile Data

You need to know who's talking? Give your agent an @username, and it fetches the full profile data for you. This structured metadata includes the user’s bio text, their current follower count, and whether or not they have a verified status badge. You can use this info to quickly assess credibility or understand the scope of influence behind an account before making any decisions about the content.

How It Works in Practice

Your AI client manages the whole process. For instance, you tell your agent: “Check out what people are saying about our new product launch,” and it automatically executes a search for keywords within the last week. If one of those tweets looks promising, you can ask it to pull the details on that specific tweet ID—getting the text, likes, retweets, and replies all in one go.

You can then follow up by asking your agent to check the profile data on the user who posted it, confirming their follower count and bio before moving on.

The server structure handles these three core functions together: searching for posts, checking out profiles, and deep-diving into individual post metrics. It keeps everything contained and structured, meaning you get clean JSON outputs every time—no messy HTML scraping needed. You just talk to your agent, and it pulls the necessary data points from X's public API.

It’s designed for social listening workflows: monitoring brand mentions, tracking competitor sentiment, or simply auditing how a piece of content performs right after it goes live. It keeps you in the loop on real-time discussions without making you write a single line of code.