OpenBiliClaw 是本地运行的跨平台个性化内容推荐 Agent，持续理解你的兴趣并主动找内容。本仓库是它的 DeepSeek Harness 插件：DSH 界面常驻第四栏（推荐/内容库/对话/画像/设置），注册 22 个 Agent Bridge 工具，让 Agent 也能读推荐、答探测、闭环学习。

本地私有、开源的自进化跨平台 AI 内容发现 Agent：先理解你，再主动从 B站、小红书、抖音、YouTube、X、知乎、Reddit、微博等平台与开放 Web 寻找内容。（支持 deepseek harness 插件） | Local-first open-source cross-platform AI content discovery agent: understands you, then proactively finds content across Bilibili, Xiaohongshu, Douyin, YouTube, X, Zhihu, Reddit, Weibo and the open web.（support deepseek harness plugin）

Run a model-diverse subagent council to investigate the same problem from multiple perspectives, compare findings, and produce a final recommendation. Use this skill whenever the user asks for a council, second opinions, multiple agents/models to evaluate one question, parallel investigation, red-te

Connects AI agents directly to AniList for anime schedules, user profile statistics, anime and manga searches, and recommendations, with optional authenticated queries and Docker/SSE support.

Enables agents to forecast airline dynamic ticket fare fluctuations and generate optimal Buy-Now versus Wait-and-Freeze recommendations via MCP.

Enables agents to forecast dynamic airline ticket fare volatility and produce optimal buy-now versus wait-and-freeze recommendations through a zero-dependency MCP STDIO interface.

Enables agents to query real-time GPU rental prices across 26 platforms, including current lowest quotes, 30-day price history, market movers, platform reliability, and task/budget recommendations. Access is read-only and metered per call via x402 with USDC on Base, requiring no signup or API key.

This MCP server enables users to analyze personal reading and media streams by computing Shannon entropy, detecting Jaccard redundancy and echo chambers, and ranking content sources by decibel SNR to produce pruning recommendations and high-signal curation.

Enables users to audit personal reading streams by quantifying category diversity with Shannon entropy, detecting lexical redundancy and echo chambers via Jaccard similarity, and ranking content sources by decibel signal-to-noise ratio for pruning recommendations.

Enables users to aggregate meal glycemic index/load, model protein and fat buffering, forecast post-prandial cognitive crash risk and focus hours, and receive macronutrient stabilization recommendations.