Select your MCP servers, choose a scope, and generate a ready-to-use configuration file. No signup required.
What Are MCP Servers?
The Model Context Protocol (MCP) is an open standard created by Anthropic that lets AI assistants like Claude Code connect to external tools, databases, and services. Think of MCP servers as plugins that extend what Claude can do. Instead of being limited to reading files and running commands, Claude Code can query your Supabase database, create GitHub issues, send Slack messages, or interact with dozens of other services directly from your terminal.
MCP works through a simple client-server architecture. Claude Code acts as the MCP client. Each MCP server is a lightweight process that exposes a set of tools (functions Claude can call), resources (data Claude can read), and prompts (templates for common tasks). The communication happens over standard I/O or HTTP, making it fast and secure. When you configure an MCP server, you are telling Claude Code how to start that server process and what credentials to use.
The protocol was open-sourced in late 2024 and has since been adopted by dozens of companies and open-source projects. As of 2026, there are over 200 community-built MCP servers available, covering everything from databases to project management tools to payment processors. This generator helps you configure the most popular ones without memorizing JSON syntax or reading documentation.
Supported MCP Servers
This tool supports configuration for the following MCP servers, each designed for a specific integration:
- Supabase -- Full access to your Supabase project including database queries, authentication management, storage buckets, and edge functions. Ideal for full-stack applications built on Supabase.
- GitHub -- Interact with repositories, issues, pull requests, code search, and GitHub Actions. Claude can create branches, review PRs, and manage issues directly.
- Slack -- Send and read messages, manage channels, search conversation history, and post notifications. Perfect for team workflow automation.
- Linear -- Create and manage issues, projects, and cycles in Linear. Claude can triage bugs, update statuses, and plan sprints.
- PostgreSQL -- Direct database access for any PostgreSQL instance. Run queries, inspect schemas, and manage data without leaving Claude Code.
- Google Drive -- Access documents, spreadsheets, and files in Google Drive. Claude can read, search, and reference your Drive content.
- Notion -- Read and write Notion pages and databases. Useful for documentation workflows and knowledge base management.
- Sentry -- Access error tracking data, view issues, analyze stack traces, and manage alerts. Essential for debugging production issues.
- Stripe -- Query payment data, manage subscriptions, and inspect webhook events. Helpful for e-commerce and SaaS applications.
- Filesystem -- Grant Claude access to specific directories outside the current project. Useful for monorepos or multi-project workflows.
Configuration Best Practices
Getting MCP configuration right from the start saves debugging time later. Follow these guidelines for a secure and efficient setup:
- Choose the right scope. Use project scope for databases and APIs specific to one project. Use global scope for tools you need everywhere, like GitHub and Slack. This keeps configurations clean and avoids conflicts.
- Secure your environment variables. Never commit API keys or tokens to version control. Store them in a
.env file that is listed in your .gitignore, or use your operating system's keychain. For teams, use a shared secrets manager like 1Password or HashiCorp Vault.
- Use least-privilege tokens. When creating API tokens for MCP servers, grant only the permissions that Claude needs. A read-only GitHub token is safer than a full-access token if you only need Claude to review code. Supabase tokens should use row-level security.
- Start small and add servers gradually. Begin with one or two MCP servers and verify they work before adding more. This makes it easier to identify issues when something goes wrong.
- Keep servers updated. MCP servers installed via
npx -y automatically fetch the latest version each time they run. For globally installed servers, run periodic updates to get bug fixes and new features.
- Monitor resource usage. Each MCP server runs as a separate process. If you notice high memory usage or slow responses, check which servers are running and disable any you are not actively using.
Common Questions
How many MCP servers can I run simultaneously?
Claude Code can run multiple MCP servers simultaneously. Most developers run 2-5 servers at once without any issues. The practical limit depends on your system resources and the servers themselves. Each server runs as a separate process, so memory usage scales linearly. For most setups, 10 or fewer servers is recommended.
Do MCP servers cost extra?
MCP servers themselves are free and open source. However, the services they connect to may have their own costs. For example, the Supabase MCP server is free, but your Supabase project may incur charges based on usage. The GitHub MCP server is free, but GitHub API rate limits apply. Always check the pricing of the underlying service.
What is the difference between project and global scope?
Project scope (.claude/settings.json) applies MCP servers only to a specific project directory. Global scope (claude_desktop_config.json) makes servers available across all projects. Use project scope for project-specific databases or APIs, and global scope for general tools like GitHub or Slack that you use everywhere.
How do I secure my API keys for MCP servers?
Never hardcode API keys in configuration files that are committed to version control. Use environment variables, a .env file (added to .gitignore), or a secrets manager. For team projects, use a shared secrets vault. The MCP configuration supports environment variable references so you can keep keys out of config files.
Can I use custom MCP servers?
Yes. You can build custom MCP servers using the MCP SDK in TypeScript or Python. Custom servers can connect to any API, database, or service. Add them to your configuration by specifying the command to run them and any required environment variables. The MCP protocol is open and well-documented.
Do MCP servers slow down Claude Code?
MCP servers add minimal overhead. They run as separate processes and communicate via stdio or HTTP. Claude Code only calls a server when it needs data from that service. Unused servers consume minimal memory (typically under 50MB each). The main performance factor is the latency of the underlying API calls, not the MCP layer itself.
How do I update MCP servers?
Most MCP servers installed via npx -y automatically use the latest version on each run. For servers installed globally, run npm update -g @package/server-name. Check the server's GitHub repository for changelogs and breaking changes. It is good practice to test updates in a project scope before applying them globally.
What happens if an MCP server fails or crashes?
If an MCP server crashes, Claude Code continues working normally but without access to that server's tools. You will see an error message indicating which server failed. Claude Code does not crash when a server fails. You can restart the server by restarting Claude Code or by running the /mcp command to reinitialize servers.
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