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@article{203176,
        author = {Siddhant Ajay Lilhare and Pankaj Ubale and Gaurav Kanoje},
        title = {Cross-Platform Social Media Post Automation Using Model Context Protocol (MCP): A Comprehensive Review and Proposed Architecture},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {11999-12007},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=203176},
        abstract = {Social media platforms serve as primary infrastructure for personal branding, enterprise communication, and community engagement, with active user identities exceeding 5.66 billion globally as of late 2025 [1], [2]. Despite this reach, producing platform-appropriate content for X (Twitter), Insta-gram, LinkedIn, and Facebook simultaneously remains highly labourintensive due to divergent tone expectations, character constraints, media requirements, and API complexities. Current automation solutions address only parts of this problem and generally lack AI-driven content intelligence, standardised tool integration, or meaningful privacy safeguards.
This paper reviews the literature underpinning a novel pro-posed system: AutoPost-MCP, an AI-driven, multi-agent social media automation framework built around the Model Context Protocol (MCP). Users supply a natural-language content intent; specialised agents then generate platform-tailored post variants and publish them securely via a unified interface authenticated through Google OAuth 2.0. The survey spans social media automation history, LLM-based content generation, multi-agent system design, MCP’s architecture and 2025 ecosystem growth, platform APIs with current rate limits, privacy mechanisms, and gaps in existing tools. Design choices are justified with reference to the surveyed literature, and research gaps, ethical considerations, and future directions are discussed.},
        keywords = {Model Context Protocol, social media Automation, AI Agents, Cross-Platform Publishing, Google OAuth 2.0, Large Language Models, Multi-Agent Systems, Platform APIs},
        month = {May},
        }