"How to Use the WeChat Developer Assistant" matching MCP servers:

MCP server that enables AI agents to fetch and summarize WeChat public articles, supporting export to HTML, Markdown, Obsidian, Notion, and OneNote.

Enables fetching WeChat public account articles, caching them in SQLite, and reading them as paginated Markdown via MCP, with optional DeepSeek summarization and HTML/Markdown export.

A local-first MCP server that lets agents search and summarize a user's own WeChat history, with stable pagination, bulk chat workflows, unread/event queries, and gated enrichment tools.

MCP server that converts PDF, video, web, and audio inputs into structured Markdown notes with support for checkpointing, batch processing, and Obsidian integration.

Converts syllabus documents into a searchable study knowledge base. Provides MCP tools to list available syllabi and retrieve structured summaries and extracted text.

Content writing toolkit for headline generation, readability scoring, tone analysis, outline building, and plagiarism similarity checking.

A TypeScript-based MCP server that implements a simple notes system, allowing users to create, access, and generate summaries of text notes through Claude Desktop.

This server provides a note storage system with a custom URI scheme, allowing users to add and summarize notes, with adjustable summary detail levels.

An offline MCP server that enables research tasks such as summarizing text, extracting key points, and saving/retrieving notes via a CLI client and stdio transport.

Parses WeChat public account articles to extract metadata, content, and generate AI-powered summaries with semantic analysis, viewpoint extraction, and structure analysis capabilities.

MCP server that provides 8 local RAG tools using LlamaIndex and Ollama, enabling AI-powered document querying, summarization, analysis, and comparison over PDFs, DOCX, XLSX, and CSV files.

Enables AI assistants to interact with local documents (PDF, Markdown, TXT) through tools for discovery, reading, extraction, summarization, comparison, keyword extraction, search, and analysis, ensuring privacy and offline capability.

An MCP server that provides tools, resources, and prompts for reading, writing, and summarizing research notes stored in a local flat-file database.

A Model Context Protocol (MCP) server that automates generating LinkedIn post drafts from YouTube videos. This server provides high-quality, editable content drafts based on YouTube video transcripts.

Enables natural language management of Gmail through MCP tools for searching, analyzing, summarizing, drafting, and sending emails, with AI reasoning and user confirmation for actions.

Enables fetching, searching, and summarizing WeChat public account articles through browser automation. Supports multiple output formats and provides article metadata and statistics.

A persistent document management and research assistant powered by Groq, enabling AI-driven document analysis, professional formatting, and long-term memory across sessions.

Enables Claude to read, rewrite, generate, and summarize LibreOffice Writer documents with preview-then-apply editing through MCP tools, authenticating via Claude Code login.

Enables document Q&A and knowledge retrieval through hybrid semantic and keyword search, with tools for document ingestion, chunking, summarization, PII redaction, and RAGAS-based evaluation.

Enables users to search local markdown and text files, retrieve recent GitHub commit activity, and summarize live web pages through a chat interface with dynamic tool discovery.