"Search for Unreal Engine or unreal-related content" matching MCP servers:

Provides deep source code analysis for Unreal Engine codebases, allowing AI assistants to understand C++ class structures, search code, and analyze subsystems.

Indexes Unreal Engine project C++ source, config files, dependencies, gameplay tags, replication, asset references, and log categories into a SQLite database and exposes tools for AI assistants to query structural and config info.

Indexes Unreal Engine source code into a local database, providing AI coding assistants with deep structural queries like class hierarchies, call graphs, and full-text search across all engine source files.

A code understanding and generation system designed for Galacean Engine that helps LLMs comprehend the engine architecture and generate high-quality engine code based on user intent.

Eyes for AI coding agents: deterministic MCP server that tells the LLM which CSS rule wins, in which file, on which line — and why. Cascade verdicts, blast radius, interaction timelines, pixel-perfect audits.

Provides AI agents with 200 deterministic micro-services covering code auditing, 3D/robotics, media processing, cryptography, blockchain settlement, AI safety, networking, and math, with automatic x402 USDC micropayments.

Graph RAG based context management engine for coding agents

Audits AI agent skills for safety using static, semantic, adversarial, and supply-chain analysis, providing scores and risk flags. Can be run via CLI, CI, or as an MCP tool from Claude Code, Cursor, and Codex.

A task-aware context compression layer for Agent workflows, RAG pipelines, and AI Coding assistants, reducing noisy logs, retrieval chunks, and code context into high-signal LLM inputs via CLI, Python SDK, and MCP.

Enables AI assistants to research the Asphalt 8 game engine through class-catalog lookup, Ghidra-based decompilation, notes, card writing, and quality checks, saving work to local drafts for later export and review.

A local code-intelligence engine for AI agents that indexes repositories into a PostgreSQL-backed code graph and serves structured, token-budgeted context over MCP and HTTP, enabling targeted queries on symbols, dependencies, contracts, and impact analysis.

Enables MCP clients to run provider-backed reverse-engineering and software-analysis workflows for source code, binaries, and architecture, with evidence, limits, and optional external tool integrations.

Enables MCP clients to index code repositories and run AST-aware semantic and hybrid keyword search across files, commits and branches, returning relevant code snippets with expanded file context. It handles incremental re-indexing with local embeddings and Qdrant storage, and can serve either over stdio or as a bearer-token-protected HTTP endpoint for remote or containerized use.

Enables AI agents to control Cheat Engine for memory reading/writing, scanning, debugging, and .NET/Mono game reverse engineering through 43 Chinese-language MCP tools, with thread-safe named-pipe communication.

A local-first, agent-agnostic MCP server that provides semantic search, persistent memory, and automated code review capabilities for development workflows. It leverages the Auggie SDK to offer advanced tools for codebase indexing, implementation planning, and deterministic static analysis.

A Model Context Protocol server that helps programmers understand code by providing explanations, tech stack analysis, and best practice suggestions through prompt templates.

Indexes your codebase so AI coding agents can search instead of re-reading files, saving up to 94% of tokens.

Enables SDK and MCP clients to perform repository code search and retrieval, inspect current source and related evidence, and optionally use semantic search, reranking, and web sources while keeping the calling agent in control.

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

Enables comprehensive project analysis, intelligent search with regex, multi-file editing with automatic backups, and dependency mapping, all via natural language.

Enables semantic code search across indexed code folders using vector embeddings, with support for multiple embedding providers and automatic file watching. Provides an admin UI and integrates with MCP clients for natural language code queries.

Semantic + lexical code search as an MCP server. Agents query in natural language and get back ranked file:line ranges to read precisely.

Enables querying a TypeScript repository's structure (symbols, imports/exports, references) through direct queries, avoiding repetitive grep operations.

Provides safe, read-only access to memory analysis and debugging functionality through the Model Context Protocol, allowing users to examine computer memory for software development, security research, and educational purposes.

Enables AI coding assistants to ground on real D365 F&O AOT metadata locally and offline, preventing hallucinated X++ field names and Chain of Command signatures.

Provides AI agents with architecture decision records, project conventions, and real codebase usage data so they can understand why, when, and where to use design system components.

Enables fast, low-token code search for AI coding agents via a local BM25 engine built on SQLite FTS5, with support for camelCase, snake_case, and Japanese text. Provides a stateless MCP stdio server and a Hermes adapter for multi-agent environments.

Enables blazingly fast file and content searching in large codebases using ripgrep, with intelligent filtering, fuzzy finding, and directory tree visualization while respecting .gitignore and avoiding common bloat directories.

Enables AI agents to perform semantic code search across entire codebases using natural language queries. Provides fast indexing and ranked search results with line numbers and file paths through the Seroost search engine.

Clones a Git repo into a temp directory so MCP clients can search and read files from another repo for context.