MCP servers are just plugins that connect Claude to your actual tools. File access, GitHub, databases, whatever. Here are the 10 that actually matter.
If you’re new to MCP, check out our guide on how MCP servers work first.
1. Filesystem
Read and write files. Set directory restrictions so your AI doesn’t touch sensitive stuff. Great for refactoring or batch updates across your codebase.
This is your foundation. Most useful when you need systematic changes across multiple files. Claude can understand your project structure, see how files relate to each other, and make consistent updates. The restriction system is critical - you can allowlist specific directories (like src/ but exclude config/ or .env). Without this server, you’re basically asking Claude to tell you what to type, then you do all the work.
Real use case: You’re renaming a core function used in 8 different files. Instead of doing each manually, ask Claude to update all imports, function definitions, and calls consistently.
Pro tip: Combine with Git server. Ask Claude to refactor a function across 10 files and commit with a message in one go.
2. GitHub
Create PRs, check CI status, triage issues without leaving your editor. Saves the constant alt-tab to the web.
The GitHub server does more than just create PRs. You can search issues by label, filter PRs by status, check which CI checks failed and why, read comments on security alerts, and even merge PRs after reviewing code. It’s basically giving Claude the ability to be a teammate who manages your GitHub workflow. The PR integration is deep - Claude can read code diffs, understand context, and even suggest fixes for failing CI. Learn more in our GitHub MCP overview.
What people miss: You can ask Claude to “search for all open issues with the ‘bug’ label” and it’ll list them with descriptions. Way faster than clicking through GitHub.
Pro tip: Tell Claude “draft a PR for the fix I just made” and it’ll create one with a description automatically. Then review before merging.
3. Playwright
366k weekly downloads. Turns plain English into browser tests. Works on sites you don’t own. Tests still need review though.
This is the most popular MCP server and for good reason. You describe a user flow in English and Claude generates Playwright tests. But here’s what makes it powerful: it works on any website, including production sites you don’t own source code for. You can test competitor flows, third-party integrations, or production bugs. For a deep dive, see our complete guide to testing MCP servers. The downside is AI-generated selectors can be fragile (classes change, elements move around). Tests still need human validation before adding to CI.
Important limitation: If the site changes CSS selectors or structure, tests break. Always run tests locally before committing to avoid breaking CI in production.
Pro tip: Ask Claude to “test the login flow on production” to catch real user flow bugs. Always review selectors before committing tests.
4. Fetch
Grab web content and convert to markdown. Useful for pulling docs, researching libraries, comparing approaches. Paywalls don’t work.
Simple but surprisingly useful. Fetch converts any public webpage into clean markdown that Claude can read and reason about. Great for comparing API docs across libraries or pulling stack overflow solutions into context. The markdown conversion handles most layouts well, but JS-heavy sites sometimes convert poorly. Paywalled content obviously won’t work.
Why this matters: Instead of copy-pasting docs, you just pass a URL. Claude reads the actual current docs, not your memory of what they said.
Pro tip: Pass a docs URL when asking about unfamiliar libraries. Claude reads current docs instead of relying on old training data.
5. Git
Dig through commit history. Answer questions like “who changed this?” or “when was this last modified?” Good for code archaeology.
Different from GitHub server. This one lets Claude search and analyze your Git history directly. Want to know when a specific bug was introduced? Ask Claude to search commits that touched that file. Need to understand the original intent of a function? Claude can find the commit that added it and read the message. Useful for understanding architectural decisions that aren’t documented.
What it’s good for: Understanding why code exists, not just what it does. Find who wrote a confusing line and ask in code review instead of guessing.
Pro tip: Ask “when was this function last modified and what was the original intent?” to understand code decisions better than reading it cold.
6. Toolbox for Databases (Google)
Query databases directly. MySQL, PostgreSQL, BigQuery. Let Claude write and execute SQL against your data.
This is a powerful one and requires careful setup. You configure it with database credentials and it lets Claude write and execute SQL queries. Claude handles the whole process - understanding your schema, writing valid SQL, executing it, and returning results. Best for analytics queries you’d normally write by hand. Warning: This has real power. Make sure your database credentials are read-only or heavily restricted, or use it only in controlled environments.
Security consideration: Don’t give Claude full database access. Use read-only credentials or restrict to specific tables.
Pro tip: Ask Claude to “find all users who haven’t logged in for 30 days” and it writes and runs the query. Perfect for analytics without writing SQL yourself.
7. AWS Documentation
Real-time access to AWS docs. No more googling random examples. Gets you CLI commands, IAM patterns, CloudFormation syntax.
Live connection to AWS documentation. Useful when you need current CLI syntax, best practices for security groups, or examples of CloudFormation templates. AWS docs are huge and easy to get lost in. Claude with this server can pull specific examples, current pricing info, and best practices without you digging through pages.
What it solves: AWS docs change frequently. You get current information instead of outdated blog posts from 2021.
Pro tip: Ask for specific CLI commands with current flags. Way faster than digging through docs or copying examples from 2023 blog posts.
8. Context7
Up to date library docs. Solves the “your training data is old” problem. Good when learning new frameworks or updating dependencies.
Maintains current documentation for popular libraries and frameworks. React, FastAPI, Next.js, TypeScript, etc. If you ask Claude about a React hook and it suggests deprecated syntax, having Context7 enabled means it’ll pull the latest docs instead. Especially useful for fast-moving frameworks where best practices change yearly.
When you need it most: Upgrading major versions. Claude gets confused about what changed between React 18 and 19. With Context7, it reads current docs.
Pro tip: Use when upgrading frameworks. Ask “what’s the new way to do X in React 19?” and it pulls current best practices.
9. Sequential Thinking
Claude breaks down complex problems step by step. Good for architecture decisions or debugging. Skip it for simple CRUD.
This changes how Claude thinks, not what tools it has access to. Instead of jumping straight to an answer, Claude shows its reasoning process. For complex problems this is gold. You see “I considered approach A but it has race condition X, so I’m going with approach B because…”. For simple tasks it just adds overhead and slower responses.
Use sparingly: Only turn this on when you need visibility into the thinking. Doing this for every small task slows you down.
Pro tip: Use for debugging gnarly issues. Ask “why is this race condition happening?” and see Claude’s full reasoning instead of just the answer.
10. Azure MCP
Azure logs, resource management, deployment scripts. Actually useful for debugging production issues without opening the portal.
Suite of 15+ Azure service connectors. Query logs from App Service, read metrics, manage resources, create deployments. The real power is in production debugging. Instead of logging into the Azure portal at 3am, you ask Claude for recent errors with stack traces. It pulls live data and summarizes it. You can also generate deployment scripts using current Azure SDK patterns instead of copying old examples.
What makes it valuable: Live production data. You’re not working blind when production breaks.
Pro tip: “Show me all errors in the last hour with stack traces” pulls live logs. Faster than manually digging through the Azure portal at 3am.
What You Actually Need
Don’t load everything at once. Start with:
- Filesystem
- GitHub
- Your cloud provider’s docs
Add specialized ones based on what you’re working on. That’s it.
Next Steps
Want to maximize MCP usage? Check out our guide on increasing MCP server usage for productivity tips and workflows.
For analytics and monitoring, read our post on MCP analytics and insights.
Quick Security Note
These servers touch real systems. Set restrictions. Review code. Don’t run generated commands blindly.
Join Our MCP Community
Want to discuss MCP servers, share discoveries, and learn from others building with Claude? Join our Discord community where developers share MCP setups, troubleshoot integrations, and stay updated on new servers and best practices.
Related Reading:
- Claude Code Plugins Guide - Extend Claude Code with custom plugins
- OpenAI Apps SDK Technical Guide - Compare with other AI integration approaches