A deterministic structural code map server for AI agents, giving them the shape of a codebase (imports, exports, classes, functions, signatures, comments, TODO-markers) without reading whole files into context. Powered by tree-sitter WASM grammars, it runs anywhere Node 18+ works.
Deterministic navigation maps over code AND markdown for AI agents: one MCP server, two lenses (tree-sitter TS/JS/Python + markdown). Map a whole project, read one function or one doc-section, ~99% less context. Merges codelens + docslens.
Topos scores code quality by analyzing the geometric and topological structure of program graphs, surfacing structural debt that conventional linters can't compute. Gives coding agents a medal-scored (SLOP → GOLD) feedback loop for writing cleaner, more composable code.
Enables AI coding assistants like Claude Code to perform real-time code linting and get violation summaries from tools such as ESLint, Stylelint, P3C, and Checkstyle via a local server.
Marrow is a persistent multi-project memory backend that provides AI agents with MCP tools for semantic code navigation, task backlog management, and versioned artifact storage. It enables seamless, token-optimized context sharing and asynchronous handoffs between different AI models working on the same codebase.
A deterministic MCP server for BitBake and Yocto that allows users to search, scan, and parse recipe files. It enables the extraction of raw variable assignments from .bb and .bbappend files without performing variable evaluation.
A Model Context Protocol server that automatically generates structured release notes from Git repository tags, analyzing differences between tags and saving formatted Markdown output to the .iris directory.
An MCP server for auditing and analyzing user interfaces across 20 platforms based on 30 fundamental UX laws. It provides automated code detection, platform-specific checklists, and comparative analysis to optimize design usability.
A Model Context Protocol server that analyzes and evaluates GitHub README documentation quality using advanced neural processing, providing scores and improvement suggestions.
Enables AI agents to self-govern by scanning code for hardcoded secrets, structural violations, and AI drift in real-time, providing fix packets for automatic remediation.
Enola. is a local Model Context Protocol (MCP) server. A deterministic map of your codebase for AI coding agents — the real architecture, extracted from your source, not guessed.
An MCP server that gives AI assistants deep awareness of the PyGo framework, enabling code generation, schema querying, module inspection, and registry operations through natural language.
Enables any MCP client to request an independent second opinion from a fresh Claude Code session without blocking, useful for plans, architecture, debugging, security reviews, and final checks.