"Using AI to control and access data from Home Assistant and smart home devices" matching MCP servers:

Connects AI assistants like Claude to PHP's XDebug debugger for runtime inspection, breakpoint control, and variable tracking, enabling natural language debugging of PHP applications.

Enables token-efficient structural code exploration using tree-sitter AST parsing, with tools for symbol search, outlines, source unfolding, call graphs, and related-file discovery.

Provides intelligent semantic code search using local AI embeddings, enabling natural language queries to find relevant code by meaning rather than exact keywords. Indexes codebases in the background with smart project detection and privacy-first local processing.

Enables AI assistants to perform intelligent semantic code search across codebases using local AI embeddings for meaning-based retrieval.

Enables AI coding assistants to run pre-publish security and code-quality scans across 17 categories, generate a 0–100 security score and Markdown report, quickly check critical vulnerabilities, and receive fix/refactor suggestions by finding ID.

MCP server that enables AI agents to read, edit, and create PLC projects in EcoStruxure Control Expert via COM automation.

A stateful MCP server that provides persistent memory, deterministic static analysis, and evolving conventions for AI coding assistants.

Enables AI assistants to search codebases by meaning using local AI embeddings, manage indexing and caching, switch workspaces, check server status, and look up latest package versions across multiple ecosystems.

Enables AI assistants to search local codebases semantically by meaning, automatically indexing code and returning relevant chunks even when terminology differs. It also supports package version lookup, workspace switching, reindexing, cache clearing, and server status checks.

Enables AI assistants to search codebases by meaning using local AI embeddings, along with package version lookup and runtime workspace, cache, indexing, and status management.

Enables AI coding assistants to search a local codebase semantically using AI embeddings, finding relevant code by meaning instead of exact keywords. It also provides package version lookup, manual reindexing, cache clearing, workspace switching, and server health status tools.

MCP server that reduces AI agent token usage by up to 90% through intelligent context compression. Enables efficient code exploration, multi-file refactoring, and debugging by providing tools for smart reading, searching, and managing code context.

Enables AI assistants to search a codebase by meaning using local AI embeddings, finding relevant code even when terminology differs from the query. Also provides package version lookup across 20+ registries, workspace switching, reindexing, cache clearing, and status checks.

Enables AI coding assistants to search a codebase by meaning using locally generated embeddings, so relevant code is found even when terminology differs from the query, along with package version lookup, reindexing, cache reset, workspace switching, and status tools. Indexing runs progressively in the background with CPU throttling and a SQLite cache, letting searches work immediately on large projects.

Enables AI assistants to perform intelligent semantic code search across a codebase using local AI embeddings, with tools for reindexing, cache management, workspace switching, package version lookup, and status checks.

Enables AI assistants to search code by meaning using local AI embeddings, and provides package version lookup, reindexing, cache management, workspace switching, and server status tools.

Enables AI coding assistants to search codebases by meaning using local AI embeddings, with tools for indexing, cache and workspace management, status checks, and latest package-version lookup.

Enables AI coding assistants to search codebases by meaning using local AI embeddings, and provides tools for package version lookup, reindexing, cache clearing, workspace switching, and status checks.

Enables AI assistants to perform semantic code search across local codebases using AI embeddings, with support for indexing, cache management, workspace switching, status checks, and package version lookup.

Enables AI assistants to search a codebase by meaning using locally generated embeddings, so relevant code is found even when the query's wording differs from the code. It also supports package version lookups across many ecosystems, plus reindexing, cache clearing, workspace switching, and server health checks.