"A search for coding in VHDL" matching MCP servers:

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.

A server providing programming guidelines and coding standards for multiple languages, enabling access and search of best practices for C#, Go, JavaScript, Python, and TypeScript.

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

locidx

Enables AI coding agents to intelligently index and search codebases with sub-20ms retrieval, 8x memory compression, and cross-encoder reranking via MCP stdio.

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.

Provides AI coding assistants with code search, impact analysis, task chaining, and persistent memory to turn AI demos into deliverable code.

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 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.

Provides AI coding agents with structured access to indexed codebases via semantic search, symbol analysis, and file reading tools.

Enables AI coding assistants to search a codebase by meaning with local embeddings, manage indexing, cache, workspace configuration, and status, and look up latest package versions across multiple registries.

Automatically enforces team coding standards in AI-assisted development by providing an MCP server that AI assistants can query for language-specific standards, style guides, and best practices.

An MCP server giving coding agents context-window-aware code search and safe, atomic multi-file edits — built to cut token usage on large codebases without sacrificing correctness.

Knot is a semantic and structural codebase indexer designed for AI coding agents and developers navigating large projects. It combines vector search and graph traversal to find code by meaning, analyze impact via reverse dependencies, and explore file architectures.

Adds symbol-aware semantic search to coding agents like Codex CLI and Claude Code, enabling precise codebase context via natural language queries.

MCP server for Speakeasy — Windows API emulation for binary analysis. It runs a .exe in a Wine-like sandbox and returns a structured API trace.

A FastMCP server for bounded, keyword-driven repository context search, enabling efficient codebase exploration with snippet extraction and focused code block retrieval.

Semantic code graph MCP server for coding agents

Provides a code search service via MCP, allowing AI clients to perform fast, indexed searches across large codebases using Zoekt, with support for filters like repository, language, and path.