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API Management Software

mcpbeat

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Uptime, install counts and source code checks for MCP servers, for teams choosing which server to trust

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About mcpbeat

Anyone picking a Model Context Protocol server, the kind of connector that lets an AI assistant reach tools and data, can use mcpbeat to see measured facts. Its pitch is that choosing a server should rest on measured facts rather than a directory entry.

Uptime measured every 15 minutes

mcpbeat checks over 12,000 live servers on a 15 minute cycle, so a team can see whether a server is actually responding and how consistently it has done so, instead of relying on a claim that it works.

Install figures from the package registries

For adoption, mcpbeat pulls real install counts from npm and PyPI. Those numbers show which servers other developers have really installed, which is a different signal from a star count or a listing position.

Reading the code for risky behaviour

mcpbeat also analyses source code for security-relevant behaviour, including file access and shell commands. A server that can touch files or run commands deserves a closer look before it is connected to an assistant.

Teams making a selection

The service is aimed at teams picking an MCP server who want proof that it works and is safe to use. Its headline coverage figure is 25,000 servers.

TrustList summary

mcpbeat monitors Model Context Protocol servers and reports on whether they work and whether their code is safe to use. For each server it tracks, it reports uptime, install counts and code findings. It is aimed at teams choosing an MCP server who want evidence rather than a directory listing.

Features

  • Uptime checks: pings more than 12,000 live servers every 15 minutes.
  • Install counts: pulls install figures from npm and PyPI.
  • Code analysis: checks code for what it does with files, shell commands and other security-relevant behaviour.

Who it serves

Teams choosing an MCP server who need evidence that it runs and is safe.

Key facts

  • Check interval: every 15 minutes
  • Package sources: npm and PyPI

Summary written by TrustList from the business's own published information, Nov 2026.

Trust Score

4/ 100
Trust Score: New

An earned signal from verification, reviews, awards, transparency and engagement - the vendor can't buy it.

Verification
0/100 · 20%
Reviews
0/100 · 30%
Awards
0/100 · 15%
Transparency
18/100 · 20%
Engagement
0/100 · 15%
Joining soon
Recommendations
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Complaints
Coming soon

Updated 9/16/2026

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