mq MCP Server
harehare/mq
[](https://agentrank-ai.com/tool/harehare--mq/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge) A jq-like Markdown query language for command-line processing
claude mcp add agentrank -- npx -y agentrank-mcp-server Overview
harehare/mq is a Rust tool licensed under MIT. A jq-like Markdown query language for command-line processing Topics: cli, jq, markdown, rust, repl, md, query, mcp, interpreter, language-server, scripting-language, html-to-markdown, mqlang, markdown-processor, markdown-parser.
Ranked #248 out of 24842 indexed tools.
In the top 1% of all indexed tools.
Has 1,051 GitHub stars.
Used by 40 other projects.
Has 16 contributors.
Actively maintained with commits in the last week.
Ecosystem
Score Breakdown
1,051 stars → well-known project
Last commit 1d ago → actively maintained
192/205 issues closed → responsive maintainer
16 contributors → active community
40 dependents → few downstream users
Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →
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[](https://agentrank-ai.com/tool/harehare--mq/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge) <a href="https://agentrank-ai.com/tool/harehare--mq/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge"><img src="https://agentrank-ai.com/api/v1/badge/harehare--mq" alt="AgentRank"></a> Matched Queries
From the README
<div align="center"> <a href="https://mqlang.org">Visit the site 🌐</a> — <a href="https://mqlang.org/book">Read the book 📖</a> — <a href="https://mqlang.org/playground">Playground 🎮</a> <h1>mq</h1> **Query. Filter. Transform Markdown.** mq is a command-line tool that processes Markdown using a syntax similar to jq. It's written in Rust, allowing you to easily slice, filter, map, and transform structured data. </div> > [!IMPORTANT] > This project is under active development. ## Why mq? mq makes working with Markdown files as easy as jq makes working with JSON. It's especially useful for: - **LLM Workflows**: Efficiently manipulate and process Markdown used in LLM prompts and outputs - **LLM Input Generation**: Generate structured Markdown content optimized for LLM consumption, since Markdown serves as the primary input format for most language models - **Documentation Management**: Extract, transform, and organize content across multiple documentation files - **Content ARead full README on GitHub →
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