Thread Analyzer MCP Server
Scrape and analyze replies from any public Threads post right from your AI coding agent.
README
<p align="center"> <h1 align="center">Thread Analyzer MCP Server</h1> <p align="center"> Scrape and analyze replies from any public Threads post — right from your AI coding agent. </p> </p>
<p align="center"> <a href="https://github.com/ethan-tsai-tsai/thread-analyzer/blob/main/LICENSE"><img src="https://img.shields.io/github/license/ethan-tsai-tsai/thread-analyzer" alt="License" /></a> <a href="https://github.com/ethan-tsai-tsai/thread-analyzer/stargazers"><img src="https://img.shields.io/github/stars/ethan-tsai-tsai/thread-analyzer" alt="Stars" /></a> <a href="https://pypi.org/project/thread-analyzer/"><img src="https://img.shields.io/pypi/v/thread-analyzer" alt="PyPI" /></a> <a href="https://python.org"><img src="https://img.shields.io/badge/python-3.13+-blue.svg" alt="Python 3.13+" /></a> </p>
What is this?
An MCP server that lets your AI assistant scrape a Threads post URL, then query and analyze the replies — all through natural conversation.
Instead of:
1. Manually open browser
2. Scroll through hundreds of replies
3. Copy-paste into spreadsheet
4. Manually look for patterns
Just say:
"Analyze the replies on this Threads post: https://www.threads.com/@zuck/post/ABC123"
Your AI agent handles the rest.
Features
- Network interception — Captures GraphQL API responses, not fragile CSS selectors that Meta randomizes
- Anti-detection — Randomized scroll delays, stealth browser flags, custom User-Agent
- 4 MCP tools — Scrape, list, search, and get statistics on replies
- Works with any MCP client — Claude Code, Claude Desktop, Cursor, VS Code, Windsurf, and more
MCP Tools
| Tool | Description |
|---|---|
scrape_thread(url) |
Scrape all replies from a public Threads post |
get_all_replies() |
Return all scraped replies with username and timestamp |
search_replies(keyword) |
Case-insensitive keyword search across replies |
get_reply_stats() |
Reply count, top commenters, avg length, time range |
Quick Start
Prerequisites
- Python 3.13+
- uv package manager
Installation
git clone https://github.com/ethan-tsai-tsai/thread-analyzer.git
cd thread-analyzer
uv sync
uv run playwright install chromium
Configuration
Add the server to your MCP client config:
{
"mcpServers": {
"thread-analyzer": {
"command": "uv",
"args": ["run", "--directory", "/absolute/path/to/thread-analyzer", "python", "server.py"]
}
}
}
<details> <summary><strong>Claude Code</strong></summary>
Add to your project's .mcp.json:
{
"mcpServers": {
"thread-analyzer": {
"command": "uv",
"args": ["run", "--directory", "/absolute/path/to/thread-analyzer", "python", "server.py"]
}
}
}
Or run: claude mcp add thread-analyzer -- uv run --directory /absolute/path/to/thread-analyzer python server.py
</details>
<details> <summary><strong>Claude Desktop</strong></summary>
Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):
{
"mcpServers": {
"thread-analyzer": {
"command": "uv",
"args": ["run", "--directory", "/absolute/path/to/thread-analyzer", "python", "server.py"]
}
}
}
</details>
<details> <summary><strong>Cursor</strong></summary>
Go to Cursor Settings > MCP > Add new MCP Server, then add:
{
"mcpServers": {
"thread-analyzer": {
"command": "uv",
"args": ["run", "--directory", "/absolute/path/to/thread-analyzer", "python", "server.py"]
}
}
}
</details>
<details> <summary><strong>VS Code (Copilot)</strong></summary>
Add to .vscode/mcp.json in your workspace:
{
"servers": {
"thread-analyzer": {
"command": "uv",
"args": ["run", "--directory", "/absolute/path/to/thread-analyzer", "python", "server.py"]
}
}
}
</details>
<details> <summary><strong>Windsurf</strong></summary>
Add to ~/.codeium/windsurf/mcp_config.json:
{
"mcpServers": {
"thread-analyzer": {
"command": "uv",
"args": ["run", "--directory", "/absolute/path/to/thread-analyzer", "python", "server.py"]
}
}
}
</details>
Standalone CLI
You can also use the scraper directly without MCP:
uv run python scraper.py "https://www.threads.com/@user/post/XXXXX"
# Options
uv run python scraper.py "URL" --output custom.csv --max-scrolls 50
How It Works
┌─────────────┐ MCP (stdio) ┌──────────────┐ Playwright ┌─────────────┐
│ AI Client │ ◄──────────────────► │ server.py │ ◄──────────────► │ Threads.com │
│ (Claude, │ scrape_thread() │ (FastMCP) │ GraphQL API │ (Meta) │
│ Cursor...) │ get_all_replies() │ │ interception │ │
│ │ search_replies() │ replies.csv │ │ │
│ │ get_reply_stats() │ │ │ │
└─────────────┘ └──────────────┘ └─────────────┘
- You give your AI assistant a Threads post URL
- AI calls
scrape_thread(url)via MCP - Server launches headless Chromium, navigates to the post
- Playwright intercepts GraphQL network responses containing reply data
- Server parses replies (username, text, timestamp), saves to CSV
- AI uses
get_all_replies(),search_replies(),get_reply_stats()to analyze
Anti-Detection
| Technique | Purpose |
|---|---|
| Custom User-Agent | Mimics real Chrome browser |
navigator.webdriver removal |
Hides automation flag |
AutomationControlled disabled |
Prevents Chromium detection |
| Randomized scroll delays (1.5-4.5s) | Avoids behavioral fingerprinting |
| Early stop on idle scrolls | Mimics natural browsing patterns |
Limitations
- Public posts only — Cannot access private or restricted posts
- Meta's anti-bot measures — Meta may block headless browsers; if scraping fails, try the standalone CLI in non-headless mode
- GraphQL schema changes — Meta periodically changes their API structure; the parser in
scraper.pymay need updating
Contributing
Contributions are welcome! Please open an issue or submit a pull request.
License
<p align="center"> <a href="https://star-history.com/#ethan-tsai-tsai/thread-analyzer"> <img src="https://api.star-history.com/svg?repos=ethan-tsai-tsai/thread-analyzer&type=Date" alt="Star History Chart" width="600" /> </a> </p>
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.