10 Best MCP Servers to Try Right Now (2026)

MCP servers give AI assistants access to your real tools — GitHub repos, Slack channels, databases, file systems, and more. With over 1,000 servers in the official registry, knowing which ones are worth installing is the hard part. I've tested dozens. These 10 earned a permanent spot in my workflow.

If you're new to MCP, start with our plain-English guide to what MCP is before diving into servers.

1. Filesystem Server

The most fundamental MCP server — it gives your AI assistant read/write access to files and directories on your machine. Point it at a project folder and Claude can read your code, edit files, search through documents, and create new files without you copying and pasting anything.

Install: Built into Claude Desktop. Go to Settings → MCP → Add filesystem server and select your folder.

Best for: Anyone who regularly asks AI to work with local files. Developers, writers, analysts — anyone whose work lives in folders.

Standout feature: Recursive search across your entire project. Ask Claude "find every file that mentions authentication" and it searches your whole codebase.

Limitation: Be careful with write access on production directories. Start with read-only on sensitive folders.

2. GitHub Server

Connects your AI to GitHub repositories. It can read code, create issues, open pull requests, review diffs, search across repos, and manage branches. This is the server that makes AI coding agents practical for team workflows.

Install: npx @modelcontextprotocol/server-github with a GitHub personal access token.

Best for: Developers who want AI to interact with their actual repos, not just code snippets pasted into chat.

Standout feature: PR review. Ask Claude to review a pull request and it reads the diff, understands the context, and gives specific feedback with line references.

Limitation: Token-intensive for large repos. Scope access to specific repos rather than your entire GitHub account.

3. PostgreSQL Server

Gives your AI direct read access to a PostgreSQL database. Ask questions in natural language — "show me users who signed up last week but haven't completed onboarding" — and it writes and executes the SQL, returning results in a readable format.

Install: npx @modelcontextprotocol/server-postgres postgres://user:pass@host/db

Best for: Analysts and developers who query databases regularly. Turns natural language into SQL without context-switching to a query tool.

Standout feature: Schema awareness. It reads your table structure and writes accurate joins without you explaining your data model.

Limitation: Read-only by default (which is good). Don't give write access unless you have safeguards in place.

4. Google Drive Server

Connects Claude to your Google Drive. It can search files, read documents and spreadsheets, and use Drive content as context for conversations. Ask "summarize the Q2 marketing plan" and it pulls the document directly.

Install: Requires Google OAuth setup. Follow the official readme for credentials configuration.

Best for: Teams that live in Google Workspace. Eliminates the copy-paste workflow of pulling document content into AI conversations.

Standout feature: Cross-document search. Ask a question that spans multiple documents and it finds relevant content across your Drive.

Limitation: OAuth setup is more complex than other servers. Plan 15-20 minutes for initial configuration.

5. Slack Server

Reads Slack channels, threads, and DMs. Ask Claude "what did the engineering team discuss about the migration this week?" and it searches relevant channels and summarizes the conversation. Useful for catching up on discussions you missed.

Install: Requires a Slack app with appropriate OAuth scopes. See the MCP registry for setup instructions.

Best for: Anyone drowning in Slack messages who needs AI to synthesize conversations into actionable summaries.

Standout feature: Thread summarization. Point it at a long Slack thread and get a concise summary with key decisions and action items.

Limitation: Message history access depends on your Slack plan. Free Slack limits how far back it can read.

6. Puppeteer / Browser Server

Gives your AI control of a headless browser. It can navigate to URLs, take screenshots, fill forms, click buttons, and extract content from web pages. Useful for web scraping, testing, and research tasks that require interacting with live websites.

Install: npx @modelcontextprotocol/server-puppeteer

Best for: Developers doing web scraping or testing, researchers who need to pull data from websites that don't have APIs.

Standout feature: Screenshot capability. Ask Claude to visit a page and screenshot it — useful for visual QA and competitive analysis.

Limitation: JavaScript-heavy sites can be flaky. Sites behind login walls need additional configuration.

7. Docker Server

Manages Docker containers through your AI. List running containers, view logs, start/stop services, and inspect container configurations. Turns Docker management into natural language commands.

Install: Community server — check the MCP registry for the latest maintained version.

Best for: Developers managing containerized applications who want to check logs and status without remembering Docker CLI syntax.

Standout feature: Log analysis. Ask "why is the API container crashing?" and it reads the logs, identifies the error, and suggests fixes.

Limitation: Giving AI access to Docker is powerful but risky. Use on development environments, not production.

8. Notion Server

Connects to your Notion workspace. Search pages, read content, create new pages, and update existing ones. Turns Notion into a knowledge base your AI can reference during conversations.

Install: Community server with Notion API integration token required.

Best for: Teams using Notion as their knowledge base or project management tool.

Standout feature: Project context loading. Connect your project wiki and every conversation starts with full context about your product, processes, and decisions.

Limitation: Large Notion workspaces can be slow to search. Scope to specific databases or pages for better performance.

9. Linear Server

Integrates with Linear for issue tracking. Create issues, update statuses, search across projects, and generate sprint summaries. Makes AI a natural part of your project management workflow.

Install: Community server with Linear API key.

Best for: Engineering teams using Linear who want AI to help with issue triage, sprint planning, and progress reporting.

Standout feature: Sprint summary generation. Ask for a weekly status update and it pulls all closed, in-progress, and blocked issues into a structured report.

Limitation: Write access means the AI can create and modify issues. Set up appropriate scoping.

10. Figma Server

Reads Figma files, components, and design tokens. Ask Claude about your design system — "what colors does our button component use?" — and it reads directly from Figma. If you're interested in Figma's AI features more broadly, see our complete Figma AI guide.

Install: Community server with Figma API token.

Best for: Developers implementing designs who want AI to reference the actual Figma source rather than screenshots.

Standout feature: Design token extraction. Pull exact colors, spacing, and typography values from your Figma components into code.

Limitation: Read-only — which is appropriate. You don't want AI modifying your design files.

How to Choose Your First MCP Server

Start with the server that matches where you spend the most time. If you live in your code editor, start with Filesystem + GitHub. If you're in meetings all day, start with Slack. If you query databases regularly, start with PostgreSQL.

Don't install all 10 at once. Each server adds tokens to Claude's context, which can slow responses and increase costs on API plans. Start with 2-3, get comfortable, then add more as needed.

For the full picture on how MCP works and why it matters, read our plain-English MCP guide. If you want an agent that can use these servers effectively in real projects, compare Claude Code vs Codex or Cursor vs Claude Code.

Want to optimize how you talk to AI regardless of what tools are connected? Try the free Prompt Optimizer — it restructures any prompt for better results in seconds.

Frequently Asked Questions

Do MCP servers work with ChatGPT or just Claude?

MCP is model-agnostic. ChatGPT added MCP support in early 2026, and Cursor, Windsurf, and other tools also support it. Any MCP server works with any MCP-compatible host.

Are MCP servers free?

Most community MCP servers are free and open source. The tools they connect to may have their own costs (GitHub Pro, Slack paid plans, etc.), but the MCP servers themselves are typically free to install and run.

Is it safe to give AI access to my tools?

Use read-only access when possible, scope access to specific resources (repos, channels, databases), and don't connect production systems until you're comfortable. MCP supports authentication and permission scoping, but the security depends on how you configure each server.

What should I install first?

Start with Filesystem + GitHub if you build software, Slack if you're drowning in messages, or Postgres if you live in data. Then add one server at a time.

Disclosure: Some links in this article are affiliate links. We only recommend tools we've personally tested and use regularly. See our full disclosure policy.