What MCP Servers Do for Claude Code
Claude Code’s default toolset covers your local environment well. It reads files, runs commands, searches code, and reasons across your project. MCP servers extend that reach to the external services your project actually depends on.
An MCP server exposes a set of tools to Claude. When you install the GitHub MCP server, Claude gains the ability to list pull requests, create issues, fetch file contents from remote repos, and more. When you install the Postgres server, Claude can inspect your schema and run queries against your database.
The right set of MCP servers turns Claude Code into a development environment that spans your entire stack, not just your laptop.
The best MCP server is the one that removes the most friction between Claude and the service you interact with most during development.
The 10 Most Useful MCP Servers for Claude Code
1. GitHub MCP Server
Package: @modelcontextprotocol/server-github
Gives Claude read and write access to GitHub repositories, issues, pull requests, and file contents. Useful for any workflow that involves code review, issue triage, or repository management.
Best use case: PR review automation, issue triage, generating release notes from merged PRs.
2. Supabase MCP Server
Package: @supabase/mcp-server-supabase
Connects Claude to your Supabase project, exposing tables, edge functions, auth configuration, and storage buckets. Supports SQL queries and schema exploration.
Best use case: Schema-driven development, query building, RLS policy review, data seeding during development.
3. PostgreSQL MCP Server
Package: mcp-server-postgres (Python)
Direct connection to any Postgres database via a connection string. Claude can inspect tables, run queries, describe indexes, and analyze query plans.
Best use case: Database-heavy projects where you need Claude to understand your schema without pasting it into every prompt.
4. Notion MCP Server
Package: @notionhq/notion-mcp-server
Reads and writes Notion pages, databases, and blocks. Lets Claude pull project documentation from Notion as context or write structured output back to Notion pages.
Best use case: Using Notion as a living spec that Claude reads before generating code, or writing bug reports and status updates to Notion from Claude.
5. Filesystem MCP Server
Package: @modelcontextprotocol/server-filesystem
Extends Claude’s file access beyond the current project directory to any path you specify. Useful for multi-repo setups or accessing shared config directories.
Best use case: Monorepos, shared library access across projects, reading config files in non-standard locations.
6. Brave Search MCP Server
Package: @modelcontextprotocol/server-brave-search
Gives Claude access to real-time web search via the Brave Search API. Claude can look up current documentation, check library versions, or research unfamiliar APIs without leaving the session.
Best use case: Researching third-party APIs, finding solutions to errors that may have been documented after Claude’s training cutoff.
7. Puppeteer MCP Server
Package: @modelcontextprotocol/server-puppeteer
Controls a headless Chrome browser. Claude can navigate URLs, take screenshots, extract content from pages, and interact with web UIs.
Best use case: End-to-end testing workflows, scraping documentation that is not available as an API, visual regression checks.
8. Slack MCP Server
Package: @modelcontextprotocol/server-slack
Reads channel history and can post messages to Slack. Useful for workflows that involve surfacing development context from Slack conversations or sending notifications.
Best use case: Pulling relevant Slack threads as context for a bug investigation, posting automated summaries to engineering channels.
9. Linear MCP Server
Package: linear-mcp-server
Connects to Linear for issue tracking. Claude can read, create, and update Linear issues, pull cycle data, and understand project priorities.
Best use case: Generating Linear tickets from code review findings, pulling sprint context before planning a feature, updating issue statuses during development.
10. Sentry MCP Server
Package: sentry-mcp
Connects to Sentry for error monitoring. Claude can fetch recent errors, read stack traces, and correlate issues with code changes.
Best use case: Debugging production errors, pulling Sentry context into a debugging session without switching browser tabs.
Comparison Table
| Server | Primary use | Auth required | Read | Write | Difficulty |
|---|---|---|---|---|---|
| GitHub | Code and issues | Personal access token | Yes | Yes | Low |
| Supabase | Database and backend | Service role key | Yes | Yes | Low |
| PostgreSQL | Database | Connection string | Yes | Limited | Low |
| Notion | Documentation | Integration token | Yes | Yes | Low |
| Filesystem | Local files | None | Yes | Yes | Very low |
| Brave Search | Web search | API key | Yes | No | Low |
| Puppeteer | Browser automation | None | Yes | Yes (UI) | Medium |
| Slack | Team communication | Bot token | Yes | Yes | Medium |
| Linear | Issue tracking | API key | Yes | Yes | Low |
| Sentry | Error monitoring | Auth token | Yes | Limited | Low |
How to Evaluate a New MCP Server
The MCP ecosystem is growing quickly. New servers appear weekly. Not all of them are worth installing.
Before adding a new server, ask these four questions:
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Does it solve a real friction point? If you already copy-paste information from a service into Claude prompts regularly, an MCP server for that service will save meaningful time. If the service is rarely relevant, the server adds startup overhead without value.
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Is it actively maintained? Check the GitHub repository. Look at recent commits, open issues, and whether bug reports get responses. An unmaintained server will break when the upstream API changes.
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What write access does it have? Read-only servers carry little risk. Servers with write access to production systems deserve more scrutiny. Review what actions the server can take before enabling it.
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How does it handle credentials? Credentials should live in environment variables, not hardcoded in config files. Confirm the server follows this pattern before adding real tokens.
A small set of well-chosen, actively maintained servers is more valuable than a large set of rarely used ones.
Recommended Starting Combinations
Start with two or three servers based on your project type, verify they work, then expand.
| Project type | Recommended starting servers |
|---|---|
| Full-stack web app | GitHub + Supabase (or Postgres) |
| API-heavy backend | GitHub + Postgres + Brave Search |
| Documentation-driven team | GitHub + Notion |
| Frontend-focused | GitHub + Puppeteer + Brave Search |
| Data engineering | Postgres + Filesystem |
Frequently Asked Questions
Do I need to pay for these MCP servers?
The MCP servers themselves are free open-source packages. The underlying services may have costs: Brave Search requires a paid API key for meaningful volume, GitHub has rate limits on free accounts, and Supabase has free tiers with limits. Check the pricing for each service before relying on it in a production workflow.
How many MCP servers can I run at once?
There is no hard limit, but each server is a separate process consuming memory and CPU. In practice, running more than six or eight servers simultaneously can slow Claude Code’s startup noticeably. Install only the servers you actively use.
Can I use multiple servers of the same type, for example two different Postgres databases?
Yes. Give each server a unique key in your config and use different environment variables for each connection. Claude will have access to both and you can direct it to use the correct one by naming it in your prompt.
Where do I find new MCP servers as they are released?
The official MCP server registry is at github.com/modelcontextprotocol/servers. The Anthropic Discord and Claude Code community forums also surface new servers quickly. Check the setup guide for how to configure any new server once you find one worth trying.
Want to get MCP working across your engineering team?
Picking the right MCP servers is step one, getting them configured consistently across a team, with credentials managed securely, is where most rollouts stall. Here is how to move forward.
Path one: set it up yourself. Start with the MCP setup guide, pick one server from the list above that addresses your biggest friction point, and get it running before adding more. The Claude Code course walks through server selection and practical usage patterns.
Path two: work with Phos AI Labs. If you want MCP configured as part of a structured Claude Code rollout for your engineering team, including server selection, credential management, and workflow design, Phos AI Labs is a CCA-F certified Claude implementation partner that runs that process. Thirty minutes, no deck. Start here.