"TypeScript" matching MCP servers:

Audits a module against its test suite and reports the cases the tests are structurally unable to see, then proves each gap with a real failing test rather than a warning. Covers Python, TypeScript, JavaScript, Java, Rust and Go.

Enables AI assistants to understand and navigate codebases through structural analysis. Provides code mapping, symbol search, and impact analysis using ast-grep for accurate parsing of Python, JavaScript, TypeScript, and Go projects.

Provides JavaScript/TypeScript code intelligence via LSP, enabling goto definition, hover info, and find references through MCP tools.

Enables AI coding assistants to inspect FastAPI applications, routers, and Pydantic models, including generating TypeScript interfaces and Zod schemas and discovering backend routes without hallucination.

Enables AI agents to execute Python, TypeScript, and JavaScript code in persistent Jupyter kernels with stateful variables and imports across interactions.

Feynman's twelve-problems method as an MCP server — a persistent set of long-running problems plus an evoke loop that tests each new trick against all of them. Local, TypeScript, no LLM inside, no API key.

Provides calculator tools for mathematical operations, access to TypeScript SDK documentation, and meeting summary prompt templates through both stdio and SSE transports.

Cross-repository code knowledge graph MCP server for Java, Kotlin, JavaScript, and TypeScript. Indexes source code into embedded KuzuDB via tree-sitter and exposes 30+ tools for call-flow tracing, multi-hop taint analysis (OWASP/CWE/PCI/STIG), entry-point reachability filtering, performance hotspot detection, and license compliance — without reading source files. 95% fewer tokens vs source-read

A comprehensive MCP server for checking package versions and rating package quality across Python (PyPI), JavaScript/TypeScript (npm), Dart (pub.dev), and Rust (crates.io) ecosystems.

This project implements a Model Context Protocol (MCP) server providing Formula One racing data using the Python FastF1 library. Inspired by an existing TypeScript server, it offers similar F1 data functionalities natively in Python via FastF1.

Provides calculator tools for mathematical operations, document resources for accessing TypeScript SDK documentation, and prompt templates for generating structured meeting summaries. Built with FastMCP to demonstrate comprehensive MCP capabilities including tools, resources, and prompts in a single implementation.

Enables LLMs to run Biome formatting, linting, and assist checks on TypeScript/web projects with token-efficient, structured output, plus searchable cached Biome documentation.

Primarily to be used as a template for developing MCP servers with FastMCP in Python, PyMCP is somewhat inspired by the official everything MCP server in Typescript.

A TypeScript-based MCP server for SearXNG that allows users to create and summarize text notes using simple URIs and metadata, facilitating natural language interaction with stored content.

A headless MCP server that enables AI to create complete 2D/3D games in Cocos Creator without opening the editor or writing TypeScript code, featuring 184 tools for scene building, physics, UI, and automated testing.

Architectural Gatekeeper for AI coding. Prevents "tunnel vision" bugs by forcing the AI to verify dependencies (via AST parsing) before editing files. Supports JavaScript & TypeScript. Blocks unsafe edits until the AI proves it understands the impact

Skylos MCP server exposes static analysis as tools for AI coding agents — scan any Python, TypeScript, or Go codebase for dead code, security vulnerabilities, and quality issues directly from Claude, Cursor, or any MCP-compatible client. Returns findings with file paths, line numbers, and severity so agents can auto-fix issues in context.

A graph-powered code intelligence engine that indexes codebases into a structural knowledge graph to provide AI agents with deep context on function calls, types, and execution flows. It offers local, zero-dependency tools for hybrid search, impact analysis, and dead code detection across Python, JavaScript, and TypeScript projects.

Enables autonomous software engineering workflows by routing intent to specialized modes, managing Fable5 task ledgers and backend contracts, auditing React/TypeScript stacks, generating architectural SVG diagrams, and enforcing write-guard path policies.

Exposes Language Server Protocol (LSP) features as MCP tools, enabling IDE-grade semantic navigation including go-to-definition, find references, hover info, and symbols across multiple programming languages (Python, Rust, C/C++, TypeScript/JavaScript, React, HTML, CSS).