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

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.

TypeScript-based MCP server designed to enhance code editing experiences by providing features such as hover information, code completion, and diagnostics.

Enables AI agents to identify what language text is written in, returning top matches, confidence scores, script detection, and character statistics via a pay-per-call x402 API without requiring an API key.

Enables AI coding agents to interact with TypeScript projects through compiler-level code intelligence, providing tools for navigation, type information, diagnostics, refactoring, and semantic search.

Enables Codex to read, write, and design windows for E-language (易语言) programs using official IDE APIs, allowing natural language control of development workflows.

Exposes VSCode's Language Server Protocol features through MCP, enabling AI assistants to perform language-aware operations like symbol navigation, reference tracking, safe renaming, type information retrieval, and hover documentation across codebases.

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.

An MCP server for learning Swedish language, providing tools for vocabulary, grammar, translations, and practice exercises.

Read-only MCP server that provides Zabbix monitoring data to AI agents, enabling investigation of hosts, metrics, incidents, and triggers with deterministic aggregation.

Enables intelligent image analysis using GLM-4.5V model, specializing in extracting and analyzing code from screenshots with support for file paths and clipboard input.

Enables LLM-powered agents to generate, execute, and analyze Alloy modeling language code for software modeling and formal verification. Provides tools to run Alloy models, access documentation and examples, and generate models from system descriptions.

Enables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.

AST-aware codebase indexing with semantic search, exposed as an MCP server. Enables semantic search and file context retrieval across your codebase using natural language queries.

Enables Claude to write in your personal style by learning from your local documents. It provides statistical style context for natural language rewriting, all without any data leaving your machine.

Enables mathematical computation via Wolfram Language/Mathematica integration, supporting calculations, equation solving, calculus, matrix operations, and symbolic mathematics.

Enables governed, read-only investigations of Amazon Athena access logs by searching exact user, IP, or correlation indicators and summarizing activity by correlation ID, with parameterized queries, validation, and result limits.

Read-only MCP server that converts Elasticsearch logs into citable evidence for AI agents, offering deterministic log summarization and search tools.

MCP server that provides OpenRouter model pricing data, enabling price lookups, trending/cheapest lists, and model searches without an API key.

An MCP server that acts as an AI mentor for any codebase using dual-layer indexing, enabling codebase initialization, tutorial generation, and semantic search.

An MCP server that allows coding agents to look up contextual rules and patterns on demand, providing just-in-time guidance for specific tasks like writing tests or authoring UI.