"A search assistant for finding Hisense air conditioners" matching MCP servers:

EU AI Act compliance scanner for Python AI agents. Scans, analyzes, and remediates LangChain/CrewAI/AutoGen/OpenAI code across 6 articles with 10 MCP tools including prompt injection detection, risk classification, and fix code generation.

Enables IDA Pro to run as a persistent, multi-agent analysis service with background jobs, allowing clients to submit binaries and query results without keeping the session open.

Automatically analyzes Python codebases and generates professional documentation including README, API docs, and setup guides.

An advisory and generative copilot for Terraform that reviews existing scripts and generates compliant infrastructure using organization-specific rules.

Generates and maintains grounded, enterprise-grade documentation for any codebase by analyzing real project artifacts, ensuring every claim is traceable to actual findings.

Analyzes code changes using static code-graph and git co-change history to identify likely affected files, returning tiered confidence reports with evidence. Exposes tools for AI assistants to inspect current changes, static impact, historical co-change patterns, and detailed explanations.

An MCP server that automates code review by providing syntax checking, code explanation, and improvement suggestions using a multi-agent system.

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

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Enables AI coding agents to perform semantic code search locally, finding code by meaning rather than exact keywords.

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 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.

MCP server for interacting with GitHub pull requests and issues via natural language. Provides tools to list PRs, inspect diffs, check CI status, and post review comments with write-safety guards.

Provides access to SvelteKit and Tailwind CSS documentation, code snippets, and component examples with secure file operations and caching for building modern web applications.

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.

Integrates Google's Gemini AI models into Claude Code and other MCP clients to provide second opinions, code comparisons, and token counting. It supports streaming responses and multi-turn conversations directly within your existing AI development workflow.

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.

Enables AI coding assistants to semantically search codebases by meaning rather than exact text, with zero external daemons and fully local embeddings. Works out-of-the-box with Claude Code, Gemini CLI, Antigravity, and Cursor.