"General Information or Concepts About Thinking" matching MCP servers:

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.

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

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 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.

MCP server that brings Octopus AI code review into editors, allowing review of code changes and asking questions about your codebase. Integrates with Cursor, Claude, or any MCP client via natural language.

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

Enables any general-purpose agent to mod IL2CPP, Mono (.NET), and Unreal games by resolving hook targets from engine metadata rather than memory guessing. Provides 45 tools covering the full workflow of finding a game, indexing types/fields/methods, injecting a Frida probe, hooking methods, and reading or writing game memory.

Provides coding agents with hybrid semantic and exact-identifier search across VHDL source, documentation, and general code, with cross-referencing and exact source attribution.

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

Provides educational tools for developers to learn programming concepts, review code, get best practices, compare approaches, generate learning paths, debug, explain code, and quiz themselves.

Extract domain knowledge from codebases to reduce LLM token consumption by 20x and time in agentic search by 10x — gathers and makes concepts, naming conventions, and vocabulary queryable via MCP.

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

A codebase ontology and a cited wiki, both kept as Markdown in one folder on your disk. Typed graph answers — what a change affects, how two concepts connect, which wiki lines lack a citation — and every write lands as a Git diff a person reviews.

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

MCP server for DeepSeek AI models (Chat + Reasoner). Supports multi-turn sessions, model fallback with circuit breaker, function calling, thinking mode, JSON output, multimodal input, and cost tracking.

Blindspot is a local, general-purpose context engine for AI coding agents. It helps agents understand project structure, symbols, relationships, and change impact before editing.

Enables storing and querying structured information about software code entities (classes, functions, files) and their relationships (calls, imports) along with qualitative observations like design decisions and change rationale.

Lets AI coding agents ask a Rails app about itself: 35 read-only tools answer from the schema, models, routes, controllers, views, jobs and conventions, over MCP or the command line, even when the app cannot boot.

Exposes Lachesis's code navigation tools over MCP, letting LLM agents ask precise compiler-level questions about dataflow, taint, callers, and guards in source code.

An MCP server for gitingest. It allows MCP clients like Claude Desktop, Cursor, Cline etc to quickly extract information about Github repositories including repository summaries, project directory structure, file contents, etc

Enables Claude to use Google Gemini as a secondary AI through MCP for large-scale codebase analysis and complex reasoning tasks. Supports both Gemini Flash and Pro models with specialized functions for general queries and comprehensive code analysis.

Enables Claude Code to call Gemini models through an OpenAI-compatible API, providing tools for deep analysis, brainstorming, code review, and general queries using Gemini's capabilities.

Provides tools for mapping and analyzing GitHub repositories. It allows users to set a GitHub Personal Access Token and retrieve detailed information about a specified repository, including its structure and summary statistics.

Enables cleaning and sanitizing prompts through an LLM-powered tool that removes sensitive information, provides structured feedback with notes and risks, and normalizes prompt formatting. Supports configurable local or remote OpenAI-compatible APIs with automatic secret redaction.

An MCP server that enables persistent memory, structured thinking sessions, and project-based knowledge management for Claude. It includes specialized coding tools for package discovery and reinvention prevention by validating code against existing libraries and APIs.