"TypeScript" matching MCP servers:

Security analysis for Python codebases through the guard-core engine: SecurityConfig validation that catches keys pydantic silently drops, docs search over the vendored corpus, live detection probing, and verified setup guidance for Python, Typescript, Rust, PHP and Go adapters.

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.

🐍 🏠 - Code graph for AI agents over MCP: resolves Python and TypeScript calls to fully qualified names and reports the share it could not resolve instead of guessing. Multi-hop impact analysis, authz reachability audit, architectural drift against declared patterns. Local, SQLite. uvx codegraph-brain

Provides a local, version-exact API index for installed Python and TypeScript packages, enabling accurate lookups and static code checking that catches hallucinated or misused APIs without executing the code.

Enables semantic code search by matching natural-language questions against LLM-written summaries of every function and returning pointers (symbol, file, line range) instead of source code. Supports summary, raw-code, and hybrid search modes across Python, Go, TypeScript/TSX, JavaScript, and C++ repositories.

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.

Record Python/Rust/TypeScript program runs to local SQLite; query call trees, exceptions, and value flow over MCP — refuses rather than guesses. Not the unrelated Telegram sensorium-mcp.

Enables AI coding agents to fetch live MDN Web Docs pages, TypeScript handbook content, and npm package metadata as clean markdown, with local search, caching, and polite throttling.

Enables AI agents to navigate JS/TS/HTML/CSS code through TypeScript, HTML, and CSS language servers, answering hover, definition, references, symbol search, outline, and diagnostics queries. Adds a cross-file index of CSS custom properties and #id/.class selectors that single-file language servers cannot provide.

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

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.

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.

Enables MCP-compatible agents to audit an entire repository through one question, detecting stacks and running parallel checks for dead code, dependencies, security, CVEs, complexity, and lint across Laravel/PHP, Python, TypeScript/React, and Flutter/Dart. It returns normalized, severity-sorted findings with false positives flagged and secret values kept out of the output.

Connects AI coding agents in the Antigravity CLI to native language servers for C#, C/C++, TypeScript/JavaScript, and Python through MCP tools, enabling precise symbol navigation, diagnostics, references, refactoring previews, and other code intelligence.

Enables users to build and continuously refresh a code index of a repository, then query it to answer architecture, impact, tracing and log questions with verifiable evidence lines. Also checks Java, Kotlin and TypeScript/JavaScript names against real sources and classpaths, and supports commit review and Minecraft/JVM analysis directly from an agent session.

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.

Enables AI clients to call the documented APIs of real business platforms—job boards, freelance marketplaces, ad networks, e-commerce, messaging, social, sales, trading and market data—through a single CLI and runtime. Serves 455 catalogued platforms with one shared verb vocabulary per category, in both Python and TypeScript.

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

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 AI agents to spin up real Linux desktops in Docker and drive them by reading windows, pages, and documents as text and acting with tools like opening apps, running menu commands, filling file dialogs, and exporting files. It exposes these capabilities uniformly over MCP, function calling, HTTP, CLI, and Python/TypeScript SDKs, with token-efficient diffs, code mode, and parallel or forked desktops.