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Best MCP Servers for JavaScript Developers in 2026

Top MCP servers for JavaScript and TypeScript developers. From Node.js debugging to browser automation, API testing, and npm package management — build faster with AI that knows your stack.

By MyMCPTools Team·

JavaScript is the language of the web — and JavaScript developers juggle more moving parts than almost any other stack. Frontend frameworks, Node.js backends, browser APIs, npm ecosystems, REST/GraphQL clients, and build toolchains all live in the same codebase. MCP servers can plug your AI assistant directly into this environment: not just as a code completer, but as an active participant that can run tests in a browser, query a local database, inspect your git history, and search npm documentation in real time.

This guide covers the best MCP servers for JavaScript and TypeScript developers in 2026 — whether you're building React SPAs, Node.js APIs, full-stack Next.js apps, or browser extensions.

1. Filesystem MCP Server — Project Navigation Across Monorepos

Modern JS projects are frequently monorepos: multiple packages, shared configs, nested node_modules, and framework-specific directory conventions that vary between Next.js, Remix, Astro, and Vite setups. The Filesystem MCP server gives your AI a complete map of your project structure — not just the files you've opened.

JavaScript-specific use cases:

  • Understanding a Next.js project's app vs pages directory split without manual exploration
  • Reading package.json, tsconfig.json, and .eslintrc across multiple workspace packages
  • Navigating shared component libraries and their relationship to consuming apps
  • Finding all usages of a deprecated import before refactoring

Setup:

{
  "mcpServers": {
    "filesystem": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-filesystem", "/path/to/your/project"]
    }
  }
}

2. Playwright MCP Server — Browser Automation and E2E Testing

The Playwright MCP server is particularly valuable for JavaScript developers because Playwright is the dominant E2E testing framework in the JS ecosystem. Connect it to your AI and you can describe a testing scenario in plain language, have your AI write the test, run it against your localhost, and iterate on failures — all in a single conversation.

Playwright + AI workflows:

  • Describe a user flow ("user signs up, confirms email, reaches dashboard") and get a working test
  • Debug a flaky test by having your AI run it 5 times and analyze the failure pattern
  • Generate visual regression tests for a component library
  • Test accessibility by having your AI navigate with keyboard-only and audit ARIA roles
  • Write Playwright scripts for web scraping without leaving your editor

Setup:

npx @playwright/mcp@latest

3. GitHub MCP Server — PR Workflow Without Context Switching

JavaScript projects move fast — open source libraries, frontend frameworks, and npm packages all operate on rapid release cycles. The GitHub MCP server lets your AI stay current with your repository without context switching to a browser.

JS-specific workflows:

  • Search your org's repos for how a specific pattern was solved before — no more re-inventing wheel patterns
  • Have your AI review a dependency update PR and flag any breaking API changes
  • Draft release notes from merged PRs automatically using conventional commit messages
  • Search issues for known bugs before spending hours debugging a library interaction

4. Brave Search MCP Server — npm, MDN, and Framework Docs

JavaScript's ecosystem evolves constantly. React hooks introduced in 2019 have replacement patterns in 2024. Next.js app router changed how data fetching works. Vite configuration differs between major versions. The Brave Search MCP server lets your AI fetch current documentation rather than relying on training data that may be months or years out of date.

When it matters most:

  • Looking up current Next.js 15 App Router patterns (significantly different from Pages Router)
  • Checking whether a React library has updated its peer dependencies for React 19
  • Finding the current recommended approach for TypeScript strict mode configuration
  • Debugging npm peer dependency conflicts with the actual current package versions

Setup:

{
  "mcpServers": {
    "brave-search": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-brave-search"],
      "env": { "BRAVE_API_KEY": "your-key" }
    }
  }
}

5. Puppeteer MCP Server — Lightweight Browser Scripting

For simpler browser automation tasks where full Playwright test infrastructure is overkill, the Puppeteer MCP server provides a lighter-weight option. Particularly useful for scraping, PDF generation, and headless browser tasks that are common in Node.js backend work.

Node.js use cases:

  • Generate PDF reports from HTML templates without a separate service
  • Scrape JavaScript-rendered pages as part of a data pipeline
  • Screenshot pages for change detection or visual testing on a budget
  • Automate form interactions for integration testing against staging environments

6. SQLite MCP Server — Local Data and Prototyping

SQLite is the default local database for many JavaScript projects — it's embedded in Electron apps, used in Bun's native storage layer, and common in Cloudflare Workers (D1). The SQLite MCP server gives your AI direct query access to your local databases during development.

JS developer workflows:

  • Inspect Electron app local storage during debugging
  • Validate that a Drizzle ORM migration applied correctly
  • Debug a Cloudflare D1 schema locally before deploying
  • Write seed data scripts informed by your actual schema

7. Redis MCP Server — Cache and Session Inspection

Redis is common in Node.js applications for session storage, rate limiting, job queues (Bull/BullMQ), and caching. The Redis MCP server lets your AI inspect your Redis state directly — seeing what's in cache, debugging queue states, and validating that sessions are being stored correctly.

Node.js + Redis workflows:

  • Debug a BullMQ job queue by inspecting delayed, waiting, and failed jobs
  • Validate that your API cache is populating and expiring as expected
  • Check session keys during authentication debugging
  • Monitor rate limiter counters during load testing

8. Git MCP Server — Commit History as Documentation

In fast-moving JavaScript projects, understanding why code was written a certain way is often more valuable than knowing what it does. The Git MCP server gives your AI access to commit history, blame, and diffs — turning your git log into searchable context.

Particularly useful for:

  • Understanding why a specific React workaround exists ("when was this added and what bug does it fix?")
  • Tracing a performance regression to its introduction commit
  • Reviewing your own recent commits before opening a PR

Recommended Stack by JavaScript Role

Frontend developer (React/Vue/Angular): Filesystem + Playwright + GitHub + Brave Search + Git

Full-stack Next.js developer: Filesystem + GitHub + Brave Search + SQLite or PostgreSQL + Playwright

Node.js backend developer: Filesystem + GitHub + Redis + SQLite/PostgreSQL + Git + Brave Search

JavaScript tooling/DevEx engineer: Filesystem + GitHub + Git + Brave Search + Docker

Browse the full coding MCP servers directory or see Best MCP Servers for TypeScript Developers for TypeScript-specific tooling.

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🔧 MCP Servers Mentioned in This Article

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Filesystem MCP Server

sandboxed read, write, edit, move and search access to an explicit whitelist of local directories, and it is the reference implementation most other filesystem MCP servers are modelled on. Shipped by Anthropic in the official modelcontextprotocol/servers monorepo (89,000+ stars, actively maintained), it is a Node.js server published to npm as @modelcontextprotocol/server-filesystem. The part worth understanding before you install is the access-control model, because there are now two ways to grant directories and they do not compose. Method one is command-line arguments: `npx -y @modelcontextprotocol/server-filesystem /path/one /path/two`. Method two, and the one the maintainers recommend, is MCP Roots — a client that supports the roots protocol sends its roots at initialization, and those roots COMPLETELY REPLACE any directories passed on the command line, then get replaced again on every `notifications/roots/list_changed`. That means allowed directories can change at runtime without restarting the server, but it also means a roots-capable client silently overrides your CLI arguments. If the server starts with no arguments and the client either does not support roots or sends an empty list, initialization throws an error. The tool surface is broad: `read_text_file` (with mutually exclusive `head`/`tail` line windows), `read_media_file` returning base64 image/audio content blocks, `read_multiple_files` which keeps going when individual reads fail, `write_file`, `edit_file`, `create_directory`, `list_directory`, `list_directory_with_sizes`, `move_file`, `search_files`, `directory_tree`, `get_file_info` and `list_allowed_directories`. `edit_file` is the one to learn — it does line-based and multi-line pattern matching with indentation detection and preservation, returns a git-style diff with context, and supports `dryRun: true` so you can preview a change before applying it; the maintainers recommend always running a dry run first. Every operation is refused outside the allowed set, and `list_allowed_directories` is the fastest way to confirm what the server actually believes it can touch.

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GitHub MCP Server

authenticated access to the whole GitHub platform — repositories, files, branches, issues, pull requests, Actions runs, security alerts, discussions and notifications — from Claude, Cursor, VS Code, Copilot CLI and any other MCP host. There is no npm package for this server, and that trips up most people who try to install it: `@github/mcp-server` is not published to the npm registry, so any `npx` line you find for it will fail. GitHub ships it three other ways. The easiest is the hosted remote server at https://api.githubcopilot.com/mcp/, which needs no install at all — point an HTTP-transport MCP client at that URL and log in with OAuth (VS Code 1.101+, Claude Desktop, Claude Code, Cursor and Windsurf all support this). The second is the official Docker image ghcr.io/github/github-mcp-server, which is what the copy-paste command on this page runs; on github.com it now performs a browser-based OAuth login on first use and keeps the token in memory only, which is why the published Docker configs map a fixed loopback callback port (-p 127.0.0.1:8085:8085 with GITHUB_OAUTH_CALLBACK_PORT=8085) so the container can receive the callback. Prefer a token? Set GITHUB_PERSONAL_ACCESS_TOKEN instead — it takes precedence over OAuth, and the minimum useful scopes are repo, read:org and read:packages. The third is the native Go binary from the repository's releases, which needs no fixed port for the OAuth flow. GitHub Enterprise Server has no hosted option: use the local server with --gh-host or GITHUB_HOST set to your instance (include the https:// scheme — it defaults to http://, which GHES rejects). Toolsets can be narrowed with GITHUB_TOOLSETS, and an insiders channel is available at /mcp/insiders or via the X-MCP-Insiders header.

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Playwright MCP Server (ExecuteAutomation)

ExecuteAutomation's Playwright MCP Server is a community-maintained browser automation server (5,500+ GitHub stars) distinct from Microsoft's official microsoft/playwright-mcp — it leans further into test generation and visual workflows rather than pure accessibility-tree navigation. Beyond standard navigate/click/fill/screenshot tools, it can generate Playwright test code from a live browsing session, scrape full page content and structured data, execute arbitrary JavaScript in the page context, and drive API testing (GET/POST/PUT/PATCH/DELETE requests) alongside the browser tools. A standout feature is 143 real device presets for responsive testing — a single call like playwright_resize({ device: "iPhone 13" }) swaps in the correct viewport, user-agent, touch support, and device pixel ratio, and natural-language prompts like "test on iPad landscape" work directly through Claude. Install via `npm install -g @executeautomation/playwright-mcp-server`, Smithery, mcp-get, or the one-line `claude mcp add --transport stdio playwright npx @executeautomation/playwright-mcp-server` for Claude Code; VS Code one-click installers are also published. No API keys are required — it launches and drives a local Chromium/Firefox/WebKit browser directly. Choose this over Microsoft's official server when you specifically need auto-generated Playwright test scripts, JS execution, or device-emulation testing; choose Microsoft's for pure lightweight accessibility-tree page navigation. One maintenance fact the listings omit, checked against GitHub and npm on 2026-08-15: this repository has not been pushed since 2025-12-13 and npm 1.0.12 was published 2025-12-12, with 32 issues open. It is neither archived nor deprecated, so nothing warns you at install time — it installs, connects and works while its Playwright dependency drifts, whereas Microsoft's server ships continuously. Weigh the codegen, 143-preset device emulation and HTTP request tools against running an eight-month-old build. Note also that headless defaults to false on playwright_navigate, so it opens a visible browser window unless told otherwise, and that stdio-mode logging goes only to ~/playwright-mcp-server.log to keep the JSON-RPC stream clean.

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Git

Tools to read, search, and manipulate Git repositories. Full Git operations support.

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Brave Search MCP Server

The Brave Search MCP Server is the official server from Brave that gives AI assistants privacy-first web search through the independent Brave Search API — no tracking, no profiling, and results drawn from Brave's own web index rather than Google or Bing. It exposes five distinct tools that map directly to the Brave Search API endpoints: brave_web_search for general queries with pagination, freshness filters, and safe-search controls; brave_local_search for businesses, restaurants, and points of interest with automatic location filtering; brave_news_search for recent articles and current events; brave_image_search for image discovery; and brave_video_search for finding videos across the web. Authentication uses a single BRAVE_API_KEY (free tier available at brave.com/search/api) or a mounted BRAVE_API_KEY_FILE for Docker-secret setups. Install in Claude Desktop, Cursor, Windsurf, or VS Code with one npx command and choose stdio or streamable-HTTP transport. Because Brave operates its own crawler and index, the Brave Search MCP server is a strong choice for developers who want an alternative to Google-dependent search tools, need reproducible non-personalized results, or care about data privacy in agent workflows — Claude can pull fresh web context, verify facts, and research topics without leaking queries to ad-tech pipelines.

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SQLite MCP Server

conversational read and write access to any SQLite database file, plus a running business-insights memo that accumulates what the analysis turns up. It is a Python server on PyPI, not a Node one, and the difference is the single most common reason setups fail here: `@modelcontextprotocol/server-sqlite` does not exist on npm, so every npx line for it 404s. The working invocation is `uvx mcp-server-sqlite --db-path /path/to/database.db` (PyPI package mcp-server-sqlite, v2025.4.25), or the equivalent `mcp/sqlite` Docker image with a volume mounted at /mcp. The --db-path argument is required and points at the .db file; the server will create it if it is not there yet. Six tools are exposed, deliberately split by risk: read_query for SELECT only, write_query for INSERT/UPDATE/DELETE, create_table for DDL, list_tables and describe-table for schema introspection, and append_insight, which writes into a memo://insights resource that updates live as findings accumulate — that resource, not the SQL tools, is what makes this server different from a generic database connector. It also ships an mcp-demo prompt that takes a business topic, generates a plausible schema and sample data, and walks through an analysis end to end, which is the fastest way to see the memo behaviour without wiring up real data. One caveat to weigh before adopting it: this is an Anthropic reference implementation that now lives in modelcontextprotocol/servers-archived, archived on 2025-05-28. The published package still installs and runs, but it is frozen — no new features, no dependency updates, and no security patches.

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Redis MCP Server

The Redis MCP Server (redis/mcp-redis) is Redis's own natural-language interface for agentic applications, letting an AI client read and write Redis data over the Model Context Protocol. Note which one you install: the server most tutorials still point at is Anthropic's reference implementation, which now lives in modelcontextprotocol/servers-archived, and its npm package @modelcontextprotocol/server-redis is explicitly marked "Package no longer supported" with a last publish of 2025-04-25. The maintained server is a Python package instead, run with uvx --from redis-mcp-server@latest, and it covers far more of Redis than the reference one did: string, hash, list, set and sorted-set tools; JSON document tools; pub/sub with stateful channel and pattern subscriptions; Streams tools including consumer-group create, read, acknowledge and destroy; vector index management and vector search through the query engine; a docs search tool; and a server-management tool for database info. Connection is a redis:// or rediss:// URL passed as --url, or the REDIS_HOST/REDIS_PORT/REDIS_PWD/REDIS_SSL environment variables, with Redis Cluster mode behind REDIS_CLUSTER_MODE and EntraID service-principal, managed-identity and default-credential auth flows for Azure Managed Redis. There is no --read-only flag: the documented way to stop an agent writing is a Redis ACL user (ACL SETUSER readonlyuser on >pw ~* +@read -@write). Ships as a PyPI package, a GitHub install via uvx, and an official mcp/redis Docker image; stdio transport only.

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Puppeteer MCP Server

browser automation over MCP — navigate, click, fill, screenshot and run JavaScript in a real Chromium instance — but the first thing to know is that this server is archived. It was one of Anthropic's original reference servers and now lives in modelcontextprotocol/servers-archived, a repository GitHub reports as archived with no commits since May 2025. The npm package @modelcontextprotocol/server-puppeteer is still installable and still runs, and its last publish is from the same period, so treat it as frozen rather than broken: no new features, no security patches, no dependency bumps on Puppeteer itself. For new work the maintained successors are Microsoft's Playwright MCP server and ExecuteAutomation's Playwright MCP server, both of which cover the same ground with active releases. If you are maintaining an existing integration, the surface is small and easy to reason about. Seven tools: `puppeteer_navigate` (takes an optional `launchOptions` object mirroring PuppeteerJS LaunchOptions — changing it restarts the browser — and an `allowDangerous` flag that must be true before flags like `--no-sandbox` or `--disable-web-security` are accepted), `puppeteer_screenshot` (CSS selector for element shots, 800x600 default, optional `encoded` for a base64 data URI instead of binary content), `puppeteer_click`, `puppeteer_hover`, `puppeteer_fill`, `puppeteer_select`, and `puppeteer_evaluate` for arbitrary JavaScript in the page context. It also exposes two resource types the tools alone do not give you: `console://logs` for the live browser console stream and `screenshot://<name>` for captured PNGs. The README carries an explicit security caution worth repeating — the browser runs on your own machine, so it can reach local files and internal IP addresses, and should not be pointed at untrusted pages while sensitive data is reachable. The npx install opens a visible browser window; the Docker image `mcp/puppeteer` runs headless Chromium instead.

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Docker MCP Server

The Docker MCP server (ckreiling/mcp-server-docker) gives an AI assistant direct control of a Docker daemon over the Model Context Protocol: containers, images, networks and volumes, as tools rather than shell commands. It is the community server most people mean by "Docker MCP" — distinct from Docker’s own Docker MCP Gateway, which does not manage your containers at all but runs *other* MCP servers inside containers. If you want to ask Claude why the postgres container keeps restarting, you want this one; if you want a single secure endpoint in front of twenty catalog servers, you want the gateway. The tool surface is explicit and small enough to reason about: list_containers, create_container, run_container, recreate_container, start_container, fetch_container_logs, stop_container and remove_container for containers; list_images, pull_image, push_image, build_image and remove_image for images; list_networks / create_network / remove_network and list_volumes / create_volume / remove_volume for the rest. Two resource templates, docker://containers/{id}/logs and docker://containers/{id}/stats, let a client read logs and live stats by container ID or name without a tool call. It also ships a docker_compose prompt that puts the model into a plan-then-apply loop — you describe the containers you want under a project name, the model proposes a concise plan, and nothing runs until you approve it; reopening the prompt with the same project name re-reads the state of everything created under it, which is how you clean up after a lost chat. It runs on the Python Docker SDK’s from_env, so DOCKER_HOST applies: set ssh://user@host and the same server administers a remote engine. Two limits are deliberate and stated by the project — privileged options like --privileged and --cap-add/--cap-drop are not supported, and container configuration passes through the model, so no secrets belong in it.

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