"Using local LLMs for code writing, reviewing, and rule generation" matching MCP servers:

A local MCP server that indexes codebases using Tree-sitter AST parsing and LanceDB, enabling AI models to search across repositories with sub-second latency.

Safe local MCP server for Windows to list, read, search, patch, backup, and verify code files in allowed folders, with Git integration and dry-run diffs.

Offline, read-only MCP server that predicts which custom Wazuh rules wazuh-analysisd will ignore at load (missing or later-loaded if_sid, if_group, duplicates, static fields) — calibrated 15/15 against Wazuh 4.14.7. Also lists Wazuh 5.0 migration blockers.

Provides code intelligence by indexing source code into SQLite and offering MCP tools for symbol search, flow tracing, and context retrieval to assist with code navigation and understanding.

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.

A local, SQLite-backed code index for Claude Code, exposed over MCP, enabling targeted code retrieval without external APIs.

Enables sandboxed file operations via MCP tools, resources, and prompts, with a Claude CLI client and Groq-powered web UI for file CRUD, search, code review, and documentation generation.

MCP server with local vector search for your codebase. Smart indexing, semantic search, Git history — all offline.

A local MCP server that provides semantic code search for Python codebases using tree-sitter for chunking and LanceDB for vector storage. It enables natural language queries to find relevant code snippets based on meaning rather than just text matching.

embedded code search engine CLI -AST based that just works - improves speed and efficiency for coding agent

Enables efficient analysis of large codebases using Claude Code and Kimi K2.5 through the Model Context Protocol, with session caching and parallel processing to reduce costs and time.

An MCP server that provides dynamic codebase context to Claude Code through tools like hybrid search, recent changes, and symbol definitions, enhancing AI-assisted coding with local RAG.

An MCP server that provides local code quality analysis for AI coding assistants, supporting file analysis, git diff review, and full project scanning with quality scoring.

Gemini-powered MCP server for automated code review, analysis, and documentation.

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.

An MCP server for intelligently reading Java source code, supporting extraction from Maven dependencies and local projects with dual decompilers.

MCP server for comprehensive code analysis, navigation, and quality assessment across 25+ programming languages.

Enables agents to run semantic search across one or more local project directories by automatically maintaining a LAN-local Qdrant index with Ollama embeddings. Indexing, staleness checks, and incremental updates happen transparently, so users can query code by meaning without managing collections, chunks, or hashes.

Checks a code repository without running it: Safe, Works and Complete scores with an A-F grade, catching leaked keys, dangerous calls, invented or lookalike packages, broken imports and missing project files. Standard-library Python; MCP tools scan, orphans and explain.

MCP server connecting Claude Code to LM Studio, delegating token-expensive tasks to a local model while keeping the cloud model in control. It reduces cloud context usage by reading files locally and returning only the processed results.