"Using language servers like Pyright or TypeScript Language Server for codebase investigation" matching MCP servers:

Lets AI assistants act as a personal language teacher by storing a learner's vocabulary, writing stories around those words, judging translations, labeling mistakes by rule, and scheduling spaced-repetition reviews with FSRS. It also serves the agreed tutoring method to any connected assistant so teaching stays consistent across Claude, ChatGPT and Codex.

Runs a language server and provides tools for communicating with it. Language servers excel at tasks that LLMs often struggle with, such as precisely understanding types, understanding relationships, and providing accurate symbol references.

Enables household members to use Alexa+ in their own language and script, with shared lists, reminders, devices, and messages stored as spoken and rendered for each person.

An MCP server that exposes Pyright language server functionality for Python, providing tools for type checking, code completions, and finding definitions. It enables AI models to perform static analysis and code formatting through the Model Context Protocol.

A Model Context Protocol server that enables AI agents to retrieve and understand entire codebases at once, providing tools to analyze local workspaces or remote GitHub repositories.

A Model Context Protocol (MCP) server that converts natural language queries into SQL statements, allowing users to query MySQL databases using conversational language instead of writing SQL code.

Enables AI assistants to semantically search and understand code repositories using PostgreSQL with pgvector embeddings. Provides repository indexing, natural language code search, and development task management with git integration.

Enables MCP-based hybrid semantic code search over repositories, providing tools for searching code by meaning or keyword, retrieving symbol definitions, finding usages, reading chunks, and listing indexed repos.

Enables hybrid and reranked semantic search across a repository's source code, documentation, and GitHub issues.

Enables AI agents to semantically search and navigate code repositories using natural language, with support for multiple repos, incremental indexing, and no local install needed.

A minimalist indexing tool that provides AI agents with semantic search and structural AST parsing for deep codebase understanding. It enables autonomous agents to navigate large codebases predictably using vector embeddings and native language server capabilities like definition and reference tracking.

A read-only MCP server that lets a Claude chat explore your local repository and answer questions about it, returning synthesized answers with file:line references.

A language expression coach MCP server that provides native-sounding translations with cultural context, tone notes, and audio pronunciation for over 13 languages.

A local-first MCP server that indexes code repositories and enables AI assistants to search, fetch, and navigate code using BM25 hybrid retrieval, supporting common languages and tools like Codex and ChatGPT.

Provides semantic vector search over local codebases via MCP, enabling hybrid search (dense + sparse + RRF) for any MCP client like GitHub Copilot or Claude Desktop.

Enables an AI assistant to place user-approved phone calls in the callee's language through your own Bland or Twilio account, with language detection, script generation, cost estimates, and safety guard rails. Includes a preview-then-confirm gate, plus call status, transcripts, and summaries.

Enables natural language time tracking and reporting for Harvest, including automatic leave requests, project/task matching, and date parsing.

Enables LLM clients to search, read, and patch a trusted source repository with rollback-safe edits, Git operations, and allowlisted validation over stdio or OAuth-protected HTTP. Keeps secrets and arbitrary shell access out of reach while enforcing bounded batched I/O and operator-controlled workspace trust.

An MCP server that transforms a local codebase into a queryable, citation-grounded knowledge base using hybrid FAISS and BM25 retrieval, with optional reranking and swappable LLM providers.

Provides secure and efficient tools for codebase analysis, including file management, metadata retrieval, and dependency tree traversal. It allows LLMs to explore project structures and search for configuration files within a restricted root directory.