A Model Context Protocol implementation that enables AI assistants to interact with markdown documentation files, providing capabilities for document management, metadata handling, search, and documentation health analysis.
Provides intelligent manuscript analysis and writing assistance for markdown projects, including semantic search, quality checks, terminology consistency, link validation, progress tracking, and comprehensive writing statistics.
A convention-aware MCP server for managing markdown files with YAML schema validation. It enables AI agents to read, write, search, and validate markdown notes while enforcing user-defined conventions across directories like Obsidian vaults and documentation repositories.
Enables querying and updating Markdown frontmatter metadata using DuckDB SQL, with optional semantic search capabilities for finding similar documents based on content.
Provides AI assistants with the ability to lint, validate, and auto-fix Markdown files to ensure compliance with established Markdown standards and best practices.
