"author:SylphxAI" matching MCP servers:

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

Empowers AI agents to securely read and extract information (text, metadata, page count) from PDF files within project contexts using a flexible MCP tool.

Provides a universal read path for agents to extract facts, metadata, and provenance from local files and guarded remote URLs without using generative LLMs.

Reads PDF, image, or video files by sniffing format and delegating to specialized sibling MCP servers, extracting facts and metadata without LLMs.

MCP server enabling local-first web search, fetch, extract, and caching with citeable excerpts, no API key required. Supports research workflows for agents and apps.

Extracts ffprobe metadata, subtitles, scenes, and timelines from video files without frame-by-frame LLM vision, providing evidence-first reading for AI agents.

Enables AI agents to read images with metadata, OCR text, regions, and citeable evidence without relying on generative LLMs.

An MCP server for managing Linear issues, projects, teams, and milestones through the Model Context Protocol. It enables users to create, update, and list workspace resources including issue statuses, comments, and user details.

A high-performance MCP server providing lightning-fast hybrid code search using TF-IDF and vector embeddings for AI assistants. It enables real-time codebase indexing and semantic retrieval with sub-50ms latency and offline support.