productivity▌

$22

When the user asks about libraries, frameworks, or needs code examples, use Context7 to fetch current documentation instead of relying on training data.

Debug logging utility with namespace-based filtering across desktop, server, and client environments. \n \n Follows strict namespace conventions (e.g., lobe-server:[module] , lobe-desktop:[module] ) to organize logs by platform and module \n Supports format specifiers including %O for expanded objects, %s for strings, and %d for numbers \n Enable output via localStorage.debug in browsers, DEBUG environment variable in Node.js, or process.env.DEBUG in Electron \n Wildcard filtering (e.g., lobe-*

Research a prospect, then draft personalized outreach based on findings. \n \n Researches prospects first using web search by default, enhanced with optional enrichment tools (verified contact info, background) and CRM data (prior relationship context) \n Generates email drafts with personalized opening, relevant hook, and clear CTA, plus LinkedIn alternatives when email unavailable \n Supports three delivery modes: auto-create email draft if email connector enabled, output text for manual copy,

Classical machine learning with scikit-learn for classification, regression, clustering, and preprocessing. \n \n Covers supervised learning (linear models, trees, SVMs, ensembles, neural networks), unsupervised learning (K-Means, DBSCAN, PCA, t-SNE), and model evaluation with cross-validation and hyperparameter tuning \n Includes preprocessing transformers for scaling, encoding categorical variables, imputing missing values, and feature engineering \n Provides Pipeline and ColumnTransformer for

Fetch and summarize news from trusted international sources via RSS feeds.

Search GitHub code, repositories, issues, and pull requests with flexible filtering. \n \n Four search types: code, repositories, issues, and pull requests, each with full GitHub search syntax support \n Optional filtering by repository owner and name to narrow results to specific projects \n Requires GitHub personal access token configured in mcp_config.json for authentication \n Command-line interface with straightforward parameters for integration into agent workflows \n

Automatically fetches current documentation from Context7 when users ask about libraries, frameworks, or code examples. \n \n Proactively triggers on implementation queries, configuration requests, documentation lookups, library mentions, and code generation prompts in both English and Chinese \n Extracts library name and version from user queries, searches Context7 API, and selects the best match by name, trust score, and version specificity \n Fetches relevant documentation snippets and integr

Persistent, searchable memory bank for AI agents with automatic project documentation sync. \n \n Provides four core MCP tools: memory_search for querying by text/type/tags, memory_write for recording knowledge and decisions, memory_read for retrieving specific entries, and memory_stats for usage analytics \n Organizes memories by type (architecture, patterns, decisions) and supports custom tagging for flexible retrieval and organization \n Runs as an MCP server that syncs with your project work

Firebase CLI fundamentals for project setup, authentication, and service initialization. \n \n Covers authentication via Firebase CLI login, project creation with unique IDs, and service initialization through interactive prompts \n Guides setup of core Firebase services including Firestore, Functions, and Hosting with configuration file generation \n Includes self-documenting CLI help system for discovering available commands and detailed usage patterns \n Requires prior completion of firebase-