{"_id":"@andrewlwn77/instagram-research-mcp","name":"@andrewlwn77/instagram-research-mcp","dist-tags":{"latest":"1.0.0"},"versions":{"1.0.0":{"name":"@andrewlwn77/instagram-research-mcp","version":"1.0.0","type":"module","description":"MCP server for systematic Instagram competitor research with deep content discovery and outlier analysis","main":"dist/index.js","bin":{"instagram-research-mcp":"dist/index.js"},"scripts":{"build":"tsc","postbuild":"chmod +x dist/index.js","dev":"tsc --watch","start":"node 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server for systematic Instagram competitor research with deep content discovery and outlier analysis","homepage":"https://github.com/andrewlwn77/instagram-research-mcp#readme","keywords":["mcp","model-context-protocol","instagram","competitor-research","outlier-detection","deep-content-analysis","affiliate-marketing","content-analysis","systematic-research"],"repository":{"type":"git","url":"git+https://github.com/andrewlwn77/instagram-research-mcp.git"},"author":{"name":"andrewlwn77"},"bugs":{"url":"https://github.com/andrewlwn77/instagram-research-mcp/issues"},"license":"MIT","readme":"# Instagram Research MCP\n\nA user-outcome-focused MCP server for systematic Instagram competitor research and outlier content discovery, designed following Anthropic's agent tool principles and IG Profit methodology.\n\n## Design Philosophy\n\nThis MCP server consolidates 18 generic Instagram tools into 3 workflow-specific research operations, prioritizing user outcomes over technical capabilities.\n\n### Key Principles\n- **User-Outcome Focus**: Tools designed around systematic competitor research workflow\n- **Zero Hallucination**: Comprehensive parameter documentation with usage examples\n- **Token Efficiency**: Semantic responses with consolidated operations\n- **Agent Optimization**: Reduced cognitive load through workflow-specific tools\n\n## Core Functions\n\n### 1. `discover_accounts_by_hashtag`\nSystematically discover Instagram competitors by hashtag with follower filtering.\n\n**Replaces manual process**: Hashtag searching → account filtering → competitor identification\n\n```javascript\n// Example: Find medium-sized affiliate marketing accounts\n{\n  \"hashtag\": \"affiliatemarketing\",\n  \"min_followers\": 5000,\n  \"max_followers\": 50000,\n  \"limit\": 30,\n  \"sort_by\": \"engagement_rate\"\n}\n```\n\n### 2. `analyze_account_outliers`\nAutomatically detect 5x+ performing content for IG Profit \"stealing like artists\" methodology with deep content discovery.\n\n**Replaces manual process**: Content review → baseline calculation → outlier identification\n\n```javascript\n// Example: Deep viral content analysis\n{\n  \"username\": \"jonathan_montoya24\",\n  \"outlier_multiplier\": 5,\n  \"time_range_days\": 30,\n  \"max_page_depth\": 5,\n  \"min_outlier_results\": 8,\n  \"content_limit\": 50\n}\n```\n\n**Enhanced Parameters**:\n- `max_page_depth`: Multiplies content search depth (e.g., 5 = 250 posts with 50 content_limit)\n- `min_outlier_results`: Target number of viral posts to discover\n- Automatically searches deeper content for comprehensive outlier discovery\n\n### 3. `batch_account_analysis`\nProcess multiple competitors systematically with deep content discovery and CSV export for workflow integration.\n\n**Replaces manual process**: Individual analysis → comparative review → data export\n\n```javascript\n// Example: Deep batch competitor analysis\n{\n  \"usernames\": [\"jonathan_montoya24\", \"charlie_chang\", \"alex_hormozi\"],\n  \"analysis_type\": \"outliers\",\n  \"export_format\": \"csv\",\n  \"max_page_depth\": 4,\n  \"outlier_multiplier\": 3,\n  \"time_range_days\": 30\n}\n```\n\n**Enhanced Parameters**:\n- `max_page_depth`: Multiplies content search per account (e.g., 4 = 200 posts per competitor)\n- Consistent deep analysis across entire competitor set\n- Comprehensive outlier discovery for systematic competitive research\n\n## Installation\n\n```bash\nnpm install @andrewlwn77/instagram-research-mcp\n```\n\n## Configuration\n\n1. Copy environment template:\n```bash\ncp .env.example .env\n```\n\n2. Add your Instagram Social API key:\n```bash\nINSTAGRAM_SOCIAL_API_KEY=your_rapidapi_key_here\n```\n\nGet your API key from: [Instagram Social API](https://rapidapi.com/social-lens-social-lens-default/api/instagram-social-api)\n\n## Usage Examples\n\n### Competitor Discovery\n```bash\n# Find 30 medium-sized affiliate marketing accounts\ndiscover_accounts_by_hashtag(\n  hashtag=\"affiliatemarketing\",\n  min_followers=5000,\n  max_followers=50000,\n  limit=30,\n  sort_by=\"engagement_rate\"\n)\n```\n\n### Outlier Content Analysis\n```bash\n# Deep analysis for comprehensive viral content discovery\nanalyze_account_outliers(\n  username=\"jonathan_montoya24\",\n  outlier_multiplier=5,\n  time_range_days=30,\n  max_page_depth=5,\n  min_outlier_results=8\n)\n```\n\n### Batch Competitor Analysis\n```bash\n# Deep batch analysis across multiple competitors\nbatch_account_analysis(\n  usernames=[\"account1\", \"account2\", \"account3\"],\n  analysis_type=\"outliers\",\n  export_format=\"csv\",\n  max_page_depth=4,\n  outlier_multiplier=3\n)\n```\n\n## Integration with IG Profit Methodology\n\nThis MCP server is designed to work with the IG Profit \"modeling/stealing like artists\" methodology:\n\n1. **Phase 1**: Systematic competitor discovery by niche hashtags\n2. **Phase 2**: Outlier content identification (5x+ performance)\n3. **Phase 3**: Batch analysis for comparative research\n\n## Zero-Hallucination Design\n\nEvery parameter includes:\n- Clear description with business context\n- 3+ concrete usage examples\n- Realistic competitor names and scenarios\n- Enum constraints where applicable\n\nThis prevents parameter guessing and ensures consistent agent performance.\n\n## Architecture\n\nBuilt on proven Instagram Social MCP foundation with:\n- Consolidated workflow-specific operations\n- Semantic natural language responses\n- Token-efficient output formatting\n- Comprehensive error handling\n\n## Requirements\n\n- Node.js >=18.0.0\n- Instagram Social API key (RapidAPI)\n- Compatible with existing IG Profit workflow and CSV formats\n\n## License\n\nMIT","readmeFilename":"README.md","_rev":"1-ebcc3066ed98beb309e7e68c897038c0"}