LinkedIn + LiGo
LinkedIn MCP Runner is a server implementation that enables Claude AI to interact with LinkedIn, allowing users to publish posts, schedule content, analyze chats, and retrieve profile information through a set of specialized tools. Developed by Ertiqah, LLC, this Node.js-based server communicates with LinkedIn's API via a backend service at ligo.ertiqah.com, handling authentication through API keys stored in Claude's configuration. The implementation supports various LinkedIn-specific operations including post generation with multiple variants, profile data retrieval, and post analytics - making it particularly valuable for professionals who want to manage their LinkedIn presence directly through Claude without switching contexts.
真实 I/O · 已连通 ✓
启动 server · tools/list · 10 个工具 · linkedin-mcp-runner下面每个工具的字段、类型、必填项,都是我们真的把 server 启动、tools/list 拉回来的原始 JSON Schema —— 真实的工具契约。注意:下方「示例调用」是按 schema 自动生成的演示,不是真实调用的返回。
publish_linkedin_postPublish a text post to LinkedIn, optionally including media (images/videos) specified by URL.
post_textstringrequiredmediaarray{
"tool": "publish_linkedin_post",
"arguments": {
"post_text": "…"
}
}schedule_linkedin_postSchedule a text post for LinkedIn at a specific future date and time, optionally including media (images/videos) specified by URL.
post_textstringrequiredscheduled_datestringrequiredmediaarray{
"tool": "schedule_linkedin_post",
"arguments": {
"post_text": "…",
"scheduled_date": "…"
}
}publish_twitter_postPublish a text post (tweet) to Twitter.
post_textstringrequired{
"tool": "publish_twitter_post",
"arguments": {
"post_text": "…"
}
}analyze_linkedin_chatAsk questions about the user's LinkedIn profile, content, or network, with support for multi-turn conversations.
querystringrequiredconversation_historyarray{
"tool": "analyze_linkedin_chat",
"arguments": {
"query": "…"
}
}generate_linkedin_postGenerate three LinkedIn post variants from any content (article, newsletter, notes, etc.) to optimize engagement.
contentstringrequiredcontent_typestring{
"tool": "generate_linkedin_post",
"arguments": {
"content": "…"
}
}get_linkedin_postsRetrieve the user's recent LinkedIn posts with engagement metrics.
limitnumber{
"tool": "get_linkedin_posts",
"arguments": {
"limit": 0
}
}get_linkedin_profileRetrieve the user's LinkedIn profile information including headline, summary, experience, and education.
{
"tool": "get_linkedin_profile",
"arguments": {}
}set_linkedin_urlSet or update the LinkedIn profile URL to analyze. Required before using profile/posts retrieval tools if not set previously.
linkedin_urlstringrequired{
"tool": "set_linkedin_url",
"arguments": {
"linkedin_url": "…"
}
}refresh_linkedin_profileForce a refresh of the LinkedIn profile data to update any recent changes.
{
"tool": "refresh_linkedin_profile",
"arguments": {}
}refresh_linkedin_postsForce a refresh of LinkedIn posts data to capture recently published content.
{
"tool": "refresh_linkedin_posts",
"arguments": {}
}综合分
效果测评卡
进行中 · 待运行真实 I/O 已解决「输入输出是什么」;下一步接 agent 真跑,量化「效果好不好」。
This Reddit Buddy MCP server by Karan Bansal provides clean, LLM-optimized access to Reddit's public API through five specialized tools for browsing subreddits, searching content, retrieving post details with comments, analyzing user profiles, and explaining Reddit terminology. Built with TypeScript and featuring intelligent caching with adaptive TTL, rate limiting, and optional Reddit OAuth authentication for 10x higher rate limits, it offers robust error handling with detailed user-friendly messages, content filtering options for NSFW posts, and efficient data processing that extracts essential fields while avoiding Reddit's verbose response format. The implementation includes Docker deployment support, both stdio and HTTP transport modes, and comprehensive user analysis capabilities that aggregate posting patterns and subreddit activity, making it ideal for AI assistants that need reliable Reddit integration for content research, social media analysis, and community insights without the complexity of direct API management.
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Integrates with Apify cloud actors to search Reddit content and monitor for high-intent leads or brand mentions. Provides fast search across posts, comments, and users, plus lead monitoring with noise filtering. Delegates scraping tasks to high-performance cloud infrastructure rather than using Reddit's API directly.