"Sailfish OS" matching MCP servers:

Provides AI agents with powerful JavaScript/TypeScript code analysis and transformation capabilities using the tree-hugger-js library.

Enables checking project files like Dockerfile, .nvmrc, and CI workflows to determine whether pinned runtime, database, and OS versions are still supported, providing end-of-life dates, latest patches, and upgrade targets for 470+ products.

Enables AI coding agents to reverse engineer an operating system from its ISO and rebuild it component by component, exposing 39 tools over stdio for ISO fingerprinting, sandboxed QEMU VM lifecycle, PE analysis, API-surface dumps, syscall tracing, behavior diffs, component scaffolding, compat shims, app-compat testing, and knowledge-base search. It lets an agent survey a reference OS, generate clean-room specs and code, boot the rebuild, and test real applications against it.

Enables source-first orchestration and knowledge indexing with inspectable architectural capabilities through a unified MCP interface, including named-attribute retrieval and atomic knowledge ingestion.

An MCP server that provides TypeScript 7 native language server capabilities (go to definition, find references, hover types, diagnostics) to coding agents, using the Go-based tsc compiler for fast and accurate semantic analysis.

A standalone MCP server that provides TypeScript type inference and hover information using tsgo, enabling AI agents to get type details, diagnostics, references, and more without needing an editor.

Enables AI agents to navigate JS/TS, HTML, and CSS code — symbol info, outlines, callers, implementations, definitions, references, hover, and diagnostics — through bundled Node language servers. It also builds a cross-file index answering where CSS custom properties and #id/.class selectors are defined and used across stylesheets, markup, and scripts.

An MCP server that wraps terraform-ls to provide Terraform language intelligence as MCP tools, enabling AI assistants to understand and navigate Terraform codebases.

Provides evidence-backed, transactional code refactoring for JavaScript/TypeScript and other languages via MCP, enabling semantic renames, signature changes, edits, and safe bulk operations with preview, atomic apply, and rollback.

Provides structured semantic context for JavaScript/TypeScript codebases, enabling coding agents to navigate, review, and change code with explicit uncertainty.

Local repository intelligence MCP server that builds a reusable graph of code structure for AI coding agents, providing 34 network-free tools for understanding, searching, and analyzing repositories without data leaving the machine.

A JavaScript reverse engineering MCP server that enables AI coding assistants to debug and analyze JavaScript code in web pages.

A unified MCP server for JavaScript reverse engineering that provides full hook, breakpoints, script debugging, and browser automation with CDP anti-detection, supporting both ATTACH and LAUNCH modes.

Indexes commit history to create a queryable expert, providing insights into code evolution, developer intent, and hidden patterns beyond static code analysis.

Enables querying a TypeScript codebase's graph for call flows, type relationships, and symbol locations without reading file bodies.

Enables cross-repository architecture discovery and dependency routing across multi-service codebases, with automated scanning and batch AST indexing for AI agents to trace request lifecycles and navigate service boundaries.

Enables AI agents to discover open-source libraries worth reusing through multi-signal repository ranking and to search real code with sub-50ms local regex/semantic queries federated to live GitHub, grep.app, and package-registry backends. It exposes seven tools over stdio—repo search, code search, repo profile/tree, file and docs fetching, and a usage guide—with structured filters, typed pre-execution errors, and a byte-identical CLI twin.

Enables Claude Code to query a TypeScript dependency graph and retrieve the minimal set of files needed for code review, implementation, or debugging.

Serves an AI coding agent a searchable index of a codebase's existing capabilities and past incidents, so it can find and reuse what already exists before writing new code. Also exposes blast-radius analysis for shared code and lets the agent reindex the knowledge base, all via local retrieval with no model calls or API keys.

Gives your AI coding agent a bounded map of an unfamiliar TypeScript SaaS repo: where the code lives, what's risky to touch, and where the money / auth / user flows are. Provides eight MCP tools for orientation, task focus, risk assessment, and SaaS-specific observations without AST or type checking.