Markdown Rules MCP Server
github.comSummary
Ask questionsMarkdown Rules MCP Server is a tool that converts project documentation written in Markdown into intelligent AI context for AI coding tools. It aims to improve the accuracy and relevance of AI assistance by providing precise, linked, and embedded code snippets and documentation, helping AI agents understand complex codebases without vendor lock-in.
Features0/14
See allNo common features found
PricingFreemium
See allFree
- Unlimited public/private repositories
- Dependabot security and version updates
- 2,000 CI/CD minutes/month (Free for public repositories)
- 500MB of Packages storage (Free for public repositories)
- Issues & Projects
- Community support
Team
- Everything included in Free, plus...
- Access to GitHub Codespaces
- Protected branches
- Multiple reviewers in pull requests
- Draft pull requests
- Code owners
- Required reviewers
- Pages and Wikis
- Environment deployment branches and secrets
- 3,000 CI/CD minutes/month (Free for public repositories)
- 2GB of Packages storage (Free for public repositories)
- Web-based support
Enterprise
- Everything included in Team, plus...
- Data residency
- Enterprise Managed Users
- User provisioning through SCIM
- Enterprise Account to centrally manage multiple organizations
- Environment protection rules
- Repository rules
- Audit Log API
- SOC1, SOC2, type 2 reports annually
- FedRAMP Tailored Authority to Operate (ATO)
- SAML single sign-on
- Advanced auditing
- GitHub Connect
- 50,000 CI/CD minutes/month (Free for public repositories)
- 50GB of Packages storage (Free for public repositories)
Rationale
The candidate, Markdown Rules MCP Server, is a tool that helps AI coding tools (like Cursor or Claude Desktop) understand project documentation by transforming Markdown files into AI context. While it aims to improve the efficiency of AI agents in understanding codebases, it does not directly observe user workflows, analyze patterns of repetitive tasks, provide actionable suggestions for workflow optimization, or automate tasks in the same way as the described product 'Second Cursor'. Its focus is on providing relevant documentation context to AI, rather than automating desktop workflows based on observed user behavior. Therefore, none of the 'must-have' features are present.
