Enables reviewing Markdown files in a browser with inline annotations, submitting or cancelling reviews, and returning structured feedback through the review_markdown MCP tool.
A local-first markdown review tool with MCP integration, enabling AI and humans to collaboratively annotate documents inline and generate revision prompts.
An MCP server for reviewing markdown plans before AI agents implement them. Enables annotation of plans with Fix, Question, and Highlight, which AI agents can read directly through MCP.
Standalone MCP harness for cross-system process evidence, code-change impact review, and natural-language repository checkout mapping, with optional accelerators like CodeGraph.
Repository-native protocol and MCP server for coordinating work items, documentation, changelogs, and project memory between humans and AI agents, using Markdown files in a Git repository as the canonical data source.
A local-first, auditable code review MCP server that freezes Git changes, creates immutable ReviewBundles, provides role-isolated contexts for correctness, security, architecture, and test reviewers, validates structured findings, and generates deterministic JSON/Markdown reports.