A TypeScript-based MCP server that implements a simple notes system, providing resources for accessing notes via URIs, tools for creating notes, and prompts for generating summaries.
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.
An HTTP MCP server that indexes large documents into exact-line-numbered sections, enabling AI models to locate, read, summarize, and edit parts of a document without ingesting the whole file.
Enables reading unstructured meeting notes, generating meeting minutes drafts, validating them against source text, and saving approved versions through a local MCP server.
Enables sentiment analysis of text blocks using the Api Ninjas API, returning sentiment scores and overall sentiment classification for up to 2000 characters of text.
Integrates local language models (like Qwen3-8B) with MCP clients, providing tools for chat, code analysis, text generation, translation, and content summarization using your own hardware.
Enables local analysis of unstructured documents (PDF, DOCX, PPTX, SVG, PNG) by extracting text and structure with citation anchors, and verifies summaries against source material before a human approves saving a report.
Enables Claude to read and analyze PDF documents with automatic OCR processing for scanned files. Features intelligent text extraction, caching for performance, and secure file access with search capabilities.
MCP server for koreafilings.com — AI-summarized Korean DART (전자공시) corporate disclosures, paid per call in USDC via the x402 protocol on Base. Tools: get_pricing (free), get_disclosure_summary (0.005 USDC).
Lets any AI agent score and simplify its own text before it reaches a human, using Flesch readability metrics and plain-language rewrites entirely on the local machine.
Integrates Vale prose linting into AI coding assistants, enabling users to check text files for style and grammar issues using Vale's powerful linting engine. Provides automated style feedback with smart configuration discovery and rich formatted results.
Enables natural language interaction with local .docx files, allowing users to find, read, search, and summarize Word documents using friendly names and location hints.