"MDX" matching MCP servers:

Provides AI assistants with comprehensive access to Grafana's React component library, including TypeScript source code, MDX documentation, Storybook examples, test files, and design system tokens for building Grafana-compatible interfaces.

MCP server that analyzes codebases with tree-sitter and generates AGENTS.md files for AI agents.

Enables headless control of a DOSBox-X guest, including memory reading and patching, framebuffer capture, input injection, and live code tracing without interfering with the host desktop.

Lints local Markdown files or whole directory trees for broken relative links and images, empty link targets or text, heading hierarchy problems, and common README issues. Only relative targets on disk are checked, so external http(s) links are never fetched.

Provides comprehensive codebase analysis and semantic understanding through integrated knowledge graphs, enabling AI assistants to understand project structure, patterns, dependencies, and context through multiple analysis tools and format generators.

Enables LLM clients to interact with the GNU Debugger (GDB) for comprehensive debugging and binary analysis. It provides a wide range of tools for program execution control, memory examination, stack analysis, and disassembly.

Validates AGENTS.md files against the cross-vendor coding-agent spec, detecting security smells and consistency issues.

Enables secure interaction with Salesforce orgs through LLMs, providing tools for managing orgs, querying data, deploying metadata, running tests, and performing code analysis with granular access control and encrypted authentication.

Enables AI agents to explore a repository by querying a pre-built structural knowledge graph of symbols and their relationships — definitions, callers, callees, blast radius, and file-level impact — instead of grepping and reading files. This cuts the tokens spent on code exploration by roughly 96–99% while running entirely on local SQLite with tree-sitter parsing.