No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by adhikasp · MCP Server · ★ 234
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is mcp-twikit safe to install? View the security audit →
MCP-Twikit A Model Context Protocol (MCP) server for interacting with Twitter. Installation Installing via Smithery To install Twikit Twitter Search for Claude Desktop automatically via Smithery: Manual Installation Example usage Using mcp-client-cli Comparing sentiments across different twitter accounts $ llm compare 20 latest tweet directed @IndiHomeCare, @dicbn, @BiznetHome, @IDMyRepublic. What are people sentiment to the product? Do 1 search for each account I'll help you analyze the latest tweets for these internet service providers in Indonesia to understand the public sentiment. I'll use the searchtwitter function for each account. Tool Calls: searchtwitter Args: query: to:IndiHomeCare count: 20
| Stars | 234 |
| Forks | 39 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 74.9778430498008/100 |
| Open Issues | 10 |
| Last Updated | 2025-03-14 |
| Created | 2024-12-15 |
| Platforms | mcp, python |
| Est. Tokens | ~1k |
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mcp-twikit is A Model Context Protocol (MCP) server for interacting with Twitter.. It is categorized as a MCP Server with 234 GitHub stars.
mcp-twikit is primarily written in Python. It covers topics such as llm, mcp, model-context-protocol.
You can find installation instructions and usage details in the mcp-twikit GitHub repository at github.com/adhikasp/mcp-twikit. The project has 234 stars and 39 forks, indicating an active community.
mcp-twikit is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to mcp-twikit on Agent Skills Hub include atlassian-mcp-server, maverick-mcp, biomcp. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: