Glama.ai — MCP Server Registry with Security Scanning

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  <main class="card">
    <p class="eyebrow">MCP directories</p>
    <h1>Glama.ai — MCP Server Registry</h1>
    <p class="desc">
      A curated registry where developers discover, compare, and vet Model Context
      Protocol servers — with automated security scanning and quality scoring to make
      installs safer.
    </p>

    <section class="access">
      <h2>How to access</h2>
      <pre><code># Browse the registry
https://glama.ai/mcp/servers

# Add a chosen server to your client's MCP config
{
  "mcpServers": {
    "example": {
      "command": "npx",
      "args": ["-y", "some-mcp-server"]
    }
  }
}</code></pre>
    </section>

    <h2>Compatible with</h2>
    <div class="pills">
      <span class="pill">Claude Code</span>
      <span class="pill">Cursor</span>
      <span class="pill">Windsurf</span>
      <span class="pill">Any MCP client</span>
    </div>

    <a class="cta" href="https://glama.ai/mcp/servers" target="_blank" rel="noopener">
      Open the registry
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What it is

Glama.ai’s MCP server registry is a public directory for discovering and evaluating Model Context Protocol (MCP) servers. Each listing collects the server’s source repository, capabilities, and metadata so developers can browse, search, and compare options in one place instead of hunting across scattered GitHub repos.

What sets it apart is its emphasis on trust: Glama runs automated security scanning and quality assessments against listed servers, surfacing signals that help you judge whether a server is safe and well-maintained before you wire it into an AI coding tool.

How to access / install

Browse the registry directly in your browser:

https://glama.ai/mcp/servers

Glama is a directory, not a package manager — pick a server from the listing, then follow that server’s own install instructions. MCP servers are typically wired into a client via its config. For example, a generic stdio server entry looks like:

{
  "mcpServers": {
    "example": {
      "command": "npx",
      "args": ["-y", "some-mcp-server"]
    }
  }
}

Add the relevant block to your client’s MCP configuration (Claude Code, Cursor, and other MCP-aware tools each expose their own config location), then restart the client.

Good for

Discovering MCP servers across many ecosystems from a single searchable index.
Comparing servers by capabilities and maintenance signals before committing.
Vetting third-party servers with security and quality signals to reduce supply-chain risk.
Teams standardizing on a reviewed shortlist of MCP servers for their AI coding tools.