"Information about Obsidian (note-taking app or volcanic glass)" matching MCP servers:

Turns local code repositories into a queryable dependency graph built from AST parsing and git co-edit history, then exposes it alongside an Obsidian vault as persistent memory. Enables context retrieval, impact analysis of proposed changes, and curation of durable prose knowledge through full-text search and Personalized PageRank classification—all fully offline without API keys or embeddings.

MCP server for the hy-app component library, enabling AI editors to search components, retrieve APIs and examples, check platform support, access hooks and tools, and validate component usage.

Enables auto-configuration and validation of React components against a glassmorphic design token system using an AST correction engine. It supports managing UI presets, enforcing design uniformity in Monaco IDE, and exporting tokens as CSS, Tailwind, or JavaScript variables.

Enables an AI agent to reverse-engineer a compiled program with Ghidra — inspecting decompiled code, instructions, callers, memory bytes, and strings — without any source code. Every reply is labelled as fact, computed, or guess, and each claim traces back to hash-checked saved evidence.

Enables powerful code search across millions of public GitHub repositories using grep.app API, with capabilities to discover code examples, retrieve specific files, and batch fetch multiple files for learning from open source projects.

This MCP server bundles a filtered copy of the Mern-Chat-App repository and exposes tools to list, read, and search files, as well as retrieve architecture overviews and file summaries.

Deterministic code-churn measurement and AI-agent detection from the CodeDelta engine: measure churn between two directories or git refs, scan for code that runs AI agents, and get AI-authorship pointers. Runs fully locally.

Provides AI coding assistants with persistent memory, AST-based project indexing, and tools for live context management and hallucination detection. It enables saving lessons to local files, trimming conversation history, and verifying code symbols to prevent errors.

Provides AI agents with a hardened code security scanner via scan_code and scan_path, detecting leaked secrets and insecure patterns while enforcing strict path confinement and resource bounds.

Enables agents to reverse-engineer software across native binaries, managed code, Electron apps, websites, and live runtime behavior, returning findings linked to the evidence and limitations behind each conclusion. It also maintains a durable workspace where those behaviors can be inspected, questioned, compared against real execution, and exported as runnable handoffs.

Enables MCP-compatible AI assistants to inspect local application internals by analyzing JavaScript/Electron/ASAR and .NET artifacts, tracing dependencies, interfaces, and data flows, and preserving traceable evidence.

Enables querying any GitHub, GitLab, or Bitbucket repository and getting AI-generated answers about the codebase, powered by Gemini.

Enables asking natural-language questions about any GitHub repository and receiving answers grounded in the actual code, with read-only enforcement and automatic repository fetching.

Turn any code repository into a searchable Obsidian vault — then let Claude Code navigate it as a set of MCP tools.

truth is a deterministic fact-checker for the claims an AI coding agent makes about its own work.

Provides coding agents with file inventory, ranked search, location-aware reading, code packing, and note writing over the workspace folder through MCP, without involving a model.

Semantic git queries via MCP. Beyond git log — answer who/what/why about any line, file, or branch with blame, co-change, PR linkage.

Enables AI assistants to diagnose and fix iOS app issues that cause App Store rejections, such as missing privacy manifests, permission strings, and test credentials, before submission.

Enables a coding agent to get short, token-efficient answers about a project through grouped searches, focused symbol or section reads, and bounded read-only script output, with safety limits on paths, secrets, commands, and response size.

Provides access to Ant Design component library documentation and information for automated code generation. Enables searching components by category or keyword, retrieving component props, examples, API documentation, and available icons.

MCP server that provides npm package information for AI agents during TypeScript development.

Extracts deterministic architecture maps from codebases for AI agents, enabling queries about blast radius, routes, security findings, and production readiness without sending code anywhere.

Enables AI agents to search and retrieve details about Odoo code elements (models, fields, views, etc.) with exact file locations using MCP tools.

Provides coding agents with a compact map of a TypeScript/TSX codebase, enabling direct answers about symbol locations, imports, dependencies, and references while reducing token usage.

A mcp server to allow LLMS gain context about shadcn ui component structure,usage and installation

An MCP server that reverse-engineers a rebuild spec (CLAUDE.md, config, and mutation-tested tests) from an existing app, enabling coding agents to rebuild the app cleanly against that spec.

Click an element in your running web app or the iOS Simulator and say what should change; your coding agent gets the comment with the selector, DOM path, computed styles, component chain, source-file hint and a cropped screenshot. Runs locally on 127.0.0.1.

Local-first, code-aware engineering cognition for AI coding agents - persistent memory, contextual retrieval, and continuous cognition about your codebase.

Enables AI coding assistants to look up 43 structured uni-app / WeChat mini-program constraint rules by category and severity before writing code, then statically scan a project to catch inline rpx styles, WXSS wildcards, defineProps generics, missing subpackage flags, animation fill-mode bugs, and leaked secrets, internal IPs, AppIDs or server paths before release. Also provides pre-submission release checklists for app store review.

Enables local detection of protected health information in source code before it reaches LLM prompts, log statements, or analytics calls.