Comparisons
The Glama alternative with live server testing
Glama.ai indexes around 72,000 MCP servers with quality grades from A to F and tool-level sub-pages for each server. It is the most comprehensive volume play in the space and does it well. MCPVault focuses on a different layer: live runtime verification, a claim mechanic for creators and grades that reflect whether a server actually responds, not only whether its code looks maintained.
Feature comparison
Glama grades from GitHub signals. MCPVault spawns servers and runs the protocol.
Both use A-F grades, but the inputs differ: runtime vs static code analysis
MCPVault re-runs the handshake weekly and lapses the badge on failure
MCPVault lets maintainers claim, edit and control their listing
Free for verified MCPVault servers during early access
Both index individual tools. MCPVault has 26,000+.
Claude Desktop, Cursor, Windsurf, VS Code, Zed, Cline and more
Ownership/affiliation not publicly disclosed
Static code analysis vs live runtime
A server can look maintained and still not run
Glama's A to F grades are useful proxies: a server with recent commits, a clear license and good documentation is more likely to work than an archived repo. But GitHub signals cannot catch a broken dependency update, a missing environment variable in the default config or a transport bug introduced in the last release. MCPVault's verification does not analyze code at all. It spawns the server using the same command a developer would run, sends an MCP initialize request over stdio and waits for a valid response. If the server does not respond correctly, it does not get the verified badge, regardless of its GitHub score. The two approaches are complementary: MCPVault shows both the static grade and the runtime result.
When Glama is the right choice
You want the broadest possible coverage. Glama's 72,000-server index is unmatched in volume.
You are doing research across the full MCP ecosystem and need a comprehensive data set rather than a curated one.
You value Glama's tool-level detail pages and its comprehensive GitHub code-signal grading across the largest corpus.
Common questions
How is MCPVault's grade different from Glama's?
Glama computes grades from static GitHub signals: commit recency, star count, license clarity and documentation coverage. Those signals predict quality but cannot tell you whether the server runs. MCPVault uses the same signal categories and additionally spawns the server in a sandbox, completing a real MCP initialize and tools/list handshake. A server can look perfect on GitHub and fail to respond at runtime. Only MCPVault catches that.
Does Glama run the MCP servers it lists?
No. Glama's quality grades are derived from GitHub repository analysis, not live execution. MCPVault spawns verified servers in an isolated sandbox using the install or verify command, runs the MCP stdio protocol and requires the server to respond correctly before granting the verified badge.
Can I claim my listing on MCPVault if it is already on Glama?
Yes. Glama has no claim mechanic, so your listing there is always auto-generated. MCPVault lets you claim your listing with GitHub sign-in, edit the description, client compatibility, install command and more, then request live verification. Claiming is free and takes under two minutes.
How large is the MCPVault index compared to Glama?
Glama indexes around 72,000 MCP servers, which is the broadest coverage available. MCPVault indexes 5,000+ servers with a quality filter: repos under two stars with no relevant topics or descriptions are excluded. The vault prioritizes a well-maintained, navigable index over raw volume.
The quality layer that runs the servers
5,000+ servers, A-F grades, 26,000+ tool-level pages. Claim your listing free, pass live verification and earn a do-follow link.