A unified MCP server for document processing that enables creating, editing, and converting Word documents (DOCX), PDFs, Markdown, and images, with support for templates, formatting, and batch operations.
MCP server that routes natural language requests to structured tool calls using a LoRA-tuned small language model, with built-in validation, retry, and fallback recovery.
A local-first semantic search server for documents, supporting PDFs, Office files, and text/markdown, enabling natural language search via the Model Context Protocol (MCP).
An MCP server for document analysis that provides 21 tools for reading, text analysis, summarization, and data statistics, enabling AI clients to process and understand documents efficiently.
Enables AI to efficiently analyze and extract structured data from complex documents, especially Excel files, by providing tools like section reading and field mapping to reduce token usage and improve success rates.
Provides MCP tools to count, list, and read local documents in formats like PDF, DOCX, Excel, HTML, and TXT, enabling natural language-driven document statistics and content inspection via qwen_agent.
This MCP server provides secure access to databases for AI agents, enforcing authentication, authorization, human approval, logging, and notifications to prevent dangerous actions.
Local MCP server for A-share stock trading via Tonghuashun, offering account/position queries, buy/sell/cancel orders with risk controls and forced user confirmation; currently simulated with a reserved interface for real broker channels.