How to Choose MCP Servers That Won't Break Your Editor

You installed an MCP server that looked promising. Great README, interesting tool list, a few hundred GitHub stars. You added it to your config, restarted your editor, and then: nothing. The server silently failed to connect. Or worse, it connected but crashed ten minutes into your session, taking your entire MCP setup down with it. Your AI assistant lost access to every other server too, and you spent the next twenty minutes debugging someone else's broken code instead of writing your own.

This is not a rare experience. It is the default experience for anyone exploring the MCP ecosystem without a filter.

The Ugly Truth About MCP Server Quality

Here is a number that should make you cautious: there are thousands of MCP servers listed across various directories, registries, and GitHub repositories. The actual number of servers built to a production-ready standard is fewer than 50.

The MCP ecosystem exploded in late 2025 and early 2026. The protocol was new, the concept was exciting, and everybody wanted to build an MCP server. The result was predictable. There are currently over 40 YouTube-related MCP servers alone. Dozens of weather servers. Countless wrappers around APIs that already have official integrations. Many of these were weekend projects, built to learn the protocol, never intended to be maintained, and certainly never tested beyond the author's own machine.

There are no quality gates. Anyone can publish an MCP server. No review process, no minimum documentation requirements, no automated compatibility testing. The registries that list servers are aggregators, not curators. They index everything they find, which means discovering a server is easy but trusting it is hard.

This is not a criticism of the people building these servers. Most are well-intentioned developers experimenting with a new technology. But the practical consequence for you -- the person who needs a reliable MCP setup to get work done -- is that 95% of what you will find is not ready for daily use. You need a framework for separating the signal from the noise.

The 5 Red Flags: What to Avoid

Before evaluating what makes a good MCP server, learn to recognize the bad ones quickly. These red flags should make you close the tab and move on.

Red Flag 1: No Updates in 90+ Days

MCP is a fast-moving protocol. Clients update frequently, the specification evolves, and best practices shift. A server that has not been updated in three months is almost certainly broken in some way that the author has not noticed or does not care about.

Check the repository's commit history. If the last meaningful commit (not just a README tweak) was more than 90 days ago, treat the server as abandoned until proven otherwise. Stale servers accumulate subtle incompatibilities that surface as mysterious failures in your editor.

Red Flag 2: Low GitHub Stars AND Low npm Downloads

Neither metric is reliable on its own. A new server from a reputable team might have few stars. A viral server might have thousands of stars but no actual users. But when both numbers are low -- under 50 stars and under 500 weekly npm downloads -- it means the server has not been tested by a meaningful number of people.

You do not want to be the first person to discover that a server crashes when it receives an unexpected response format. Let the community find those bugs first. Servers with a larger user base have had their rough edges filed down through real-world usage and bug reports.

Red Flag 3: No Documentation or Broken README

If a server's README does not clearly explain what environment variables it needs, how to install it, and what tools it exposes, walk away. Documentation is a proxy for the author's commitment to the project. A server with no docs was built for the author, not for you.

Pay particular attention to setup instructions. If they are vague ("set your API key"), incomplete (missing required environment variables), or reference a configuration format that does not match the current version, you will waste time debugging configuration issues before you even get to evaluate whether the server is useful.

Red Flag 4: Requires Excessive Permissions

An MCP server that helps you search documentation should not need full filesystem read-write access. A server that queries an API should not need shell execution permissions. When a server requests permissions that go far beyond its stated purpose, it is either poorly designed or doing something you did not ask for.

Review the permissions a server requests before installing it. The principle of least privilege applies here: a well-designed server only asks for what it needs. Excessive permissions are a sign of sloppy architecture at best, and a security risk at worst.

Red Flag 5: No Error Handling

This one is harder to spot before installation, but it is the most disruptive when you hit it. Many MCP servers have no graceful error handling. When the external API times out, the server crashes. When it receives malformed input, it throws an unhandled exception. When the network drops momentarily, it dies and does not reconnect.

The symptoms are familiar: your AI assistant suddenly loses access to all MCP tools mid-session, or your editor hangs for 30 seconds waiting for a response that will never come. If you experience these issues consistently with a particular server, the server's error handling is broken. Remove it and find an alternative.

The 5 Green Flags: What to Look For

Now that you know what to avoid, here is what separates the top-tier MCP servers from the rest.

Green Flag 1: Official Server from the Service Provider

The single strongest signal of quality is when the MCP server is built and maintained by the team behind the service itself. Supabase maintains the Supabase MCP server. Stripe maintains the Stripe MCP server. Sentry maintains the Sentry MCP server.

These servers are better for three reasons. First, the team has intimate knowledge of their own API, so the tool implementations are correct and complete. Second, when the API changes, the MCP server gets updated in the same release cycle. Third, there is institutional commitment to keeping the server working because it is part of the product's developer experience.

When an official server exists, always prefer it over community alternatives.

Green Flag 2: Active Maintenance

Check the commit history. You want to see meaningful updates within the last 30 days. Not just dependency bumps -- actual feature additions, bug fixes, or compatibility updates.

Active maintenance means the author is using the server themselves, responding to issues, and keeping pace with changes in the MCP specification and the underlying API. It also means that if you file a bug report, someone is likely to read it.

Green Flag 3: Reasonable Token Footprint

Every tool a server exposes costs you roughly 500 tokens of context window space. A server with 10 well-designed tools costs about 5,000 tokens -- reasonable. A server with 80 tools, many of which you will never use, costs 40,000 tokens -- that is 20% of Claude's context window consumed by a single server.

The best servers expose a focused set of tools that cover their core functionality without bloat. They do not try to wrap every endpoint of an API. They surface the operations that are actually useful in an AI-assisted workflow and leave the rest out.

Green Flag 4: Minimal Permissions

A well-designed MCP server follows the principle of least privilege. A documentation search server needs read access to fetch content, nothing more. A database server needs database credentials, not filesystem access. A deployment monitoring server needs read access to deployment status, not write access to your production environment.

Check what environment variables and permissions a server requires and ask yourself whether each one is justified by what the server actually does. Fewer permissions mean a smaller attack surface and less risk.

Green Flag 5: Documented Environment Variables and Clear Setup

The best MCP servers make installation trivial. Their documentation clearly lists every required environment variable, explains where to get each credential, specifies the exact command to run, and shows example configurations for multiple AI clients.

Look for servers that include example .env files, per-client configuration snippets, and troubleshooting sections. This level of documentation indicates a mature project that has been through real user feedback cycles.

Server Evaluation Checklist

Use this table as a quick reference when evaluating any MCP server:

No server needs to be green on every metric. But if a server is red on three or more, it is not ready for daily use.

Use the Server Health Dashboard

Evaluating servers manually is tedious. That is why we built the Server Health Dashboard on StackMCP. It shows real-time maintenance status, freshness indicators, and quality metrics for every server in our catalog.

The dashboard tracks when each server was last updated, flags servers that are falling behind on maintenance, and highlights which servers are officially maintained by their service providers. Instead of checking GitHub commit histories yourself, you can scan the dashboard and immediately see which servers are healthy and which are at risk.

If you are assembling your own stack, check the dashboard first. It takes thirty seconds and can save you hours of debugging a server that was abandoned six months ago.

Use Quality Scores

Every server on StackMCP has a quality score from 0 to 100. The score is calculated from a weighted combination of objective metrics:

• GitHub stars and npm downloads -- community adoption and trust
• Freshness -- how recently the server was updated
• Official status -- whether the server is maintained by the service provider
• Token efficiency -- how many useful tools the server provides relative to its context cost
• Permissions -- whether the server follows the principle of least privilege

A score above 80 indicates a production-ready server that you can rely on. Between 60 and 80, the server is usable but may have rough edges. Below 60, proceed with caution and have a fallback plan.

Quality scores are not opinions. They are derived from data. You can use them to compare alternatives -- for example, when choosing between two database MCP servers or two browser automation servers -- and make an informed decision based on objective criteria rather than marketing copy.

The StackMCP Approach

Everything described in this article -- the red flags, the green flags, the evaluation checklist -- is what we do for every server before it enters the StackMCP catalog. We check maintenance status, review permissions, measure token footprint, verify documentation quality, and confirm that the server actually works with the clients it claims to support.

Servers that do not pass do not get listed. It is that simple.

The curated stacks take this a step further. Each stack -- whether it is the Indie Hacker stack, the Frontend Developer stack, or the Backend Developer stack -- is a combination of servers that have been individually vetted and then tested together to confirm they work without conflicts, overlapping tools, or excessive token overhead.

You can absolutely evaluate MCP servers yourself using the framework in this article. But if you would rather skip the research and start with a stack that has already been through this process, that is what stackmcp.dev is for.

Start With Trust, Not Hype

The MCP ecosystem is young and noisy. New servers appear daily, directories grow longer, and it is tempting to install everything that looks interesting. Resist that impulse.

Start with servers you can trust: official servers from service providers, actively maintained projects with real user bases, and tools that have been independently evaluated. Add servers one at a time, verify they work, and remove anything that causes instability.

Your MCP setup should be a productivity multiplier, not a source of debugging sessions. Choose servers that earn their place in your context window, and your AI assistant will be dramatically more effective for it.