"Trending MCP server for memory usage with GitHub Copilot integration" matching MCP servers:

Get hot trending topics from social media platforms like Weibo, Douyin, Bilibili, etc. via Streamable HTTP endpoint.

A headless local stdio server that gives an MCP-compatible assistant durable relationship memory for LinkedIn contacts — resumable ingestion into SQLite, source-backed labels, organizations, opportunities and follow-ups, plus revision-checked draft preparation held in an outbox. It enables evidence-based classification and reply drafting from your own approved LinkedIn API access without any automatic sending, browser automation, or telemetry.

Enables ChatGPT to connect to LinkedIn via OAuth and perform authorized actions like posting, commenting, replying, and analyzing profile/content with user approval.

Enables agents to search and read posts, images, and limited comments across Xiaohongshu, Weibo, Zhihu, and WeChat Official Accounts, with local OCR and traceable sources.

Automates posting articles to Dev.to and sharing posts on LinkedIn via command-line, cron jobs, or Copilot sessions.

Enables AI assistants to interact with the Post For Me API, allowing them to explore endpoints, make test requests, and use documentation to help integrate this SDK into your application.

Enables LinkedIn profile reads and post operations through a local-first MCP server, with OAuth token management and approval-friendly tools for OpenWorker.

MCP server for Takes, a free, open-source Mac teleprompter and recorder for talking-head videos. It lets an AI assistant write scripts and storyboards, manage takes, make edits and draft the posts for LinkedIn, X, YouTube and Shorts.

Enables MCP-capable models to read QQ messages, reply in group and private chats, send images and favorite stickers, poke users, and manage pacing, deduplication, and concurrency during ongoing chat tasks through a local SnowLuma OneBot interface.

Enables AI assistants to research and organize professional contacts, enrich profiles, sync inbox conversations, pull web context, and draft personalized outreach messages that require human approval before sending. All actions run under server-side daily and hourly safety thresholds to keep the connected LinkedIn account within safe limits.

An MCP server that lets AI assistants like Claude read LinkedIn data through your own logged-in browser session. Access profiles and companies, search for jobs, or get job details.

An MCP server that lets AI assistants like Claude read LinkedIn data through your own logged-in browser session. Access profiles and companies, search for jobs, or get job details.

MCP Server for notify to telegram / weixin

A lightweight toolkit that enables Claude to search Twitter with natural language queries and display results based on user intent, supporting features like tweet filtering, pagination, and flexible output formatting.

Connects your WordPress.com account to Claude Desktop, enabling you to read your feed, check notifications, manage tags and follows, and discover new blogs through natural conversation.

Connect Claude Desktop to WhatsApp. Send & receive messages, manage groups, share media — all through natural conversation with Claude.

Enables complete management of X (Twitter) accounts through a single API key, supporting functions like getting tweets, searching, generating and posting replies.

Live LinkedIn data for AI agents: 44 tools for profiles, companies, jobs, posts, people search, job-change signals and email finding. Hosted remote server (streamable HTTP) - your agent never touches your own LinkedIn account. 300 free credits on signup, no card. Dockerfile in repo bridges stdio clients to the hosted endpoint via mcp-remote.

Provides TikTok trend data to AI assistants, including hashtag volume, growth rates, and top trending topics for early trend detection.

AutomateLab Content Distribution publishes content across DEV.to, Hashnode, GitHub Discussions, Reddit and Bluesky, with browser workflows for LinkedIn, Medium and X. Tracks publishing state and adapts content per platform. Product and documentation: https://automatelab.tech/products/mcp/content-distribution-mcp/