A
license-
qualityC
maintenanceAudits npm packages for supply-chain attacks (typosquatting, malicious install scripts, credential exfiltration) before installation, returning a SAFE/SUSPICIOUS/DANGEROUS verdict.
Last updated
MIT
PackageGuard
Server Details
x402-gated safety checker for npm/PyPI packages before you npm install / pip install.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Glama MCP Gateway
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MCP client
Glama
MCP server
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Tool Definition Quality
A3.7/5.0
Tool DescriptionsB
Average 3.4/5 across 1 of 1 tools scored.
Server CoherenceA
Disambiguation5/5
With only one tool, there is no possibility of confusion between tools. The single tool's purpose is clear and distinct.
Naming Consistency5/5
With only one tool, naming consistency is trivially maintained. The tool name follows a clear verb_noun pattern and is descriptive.
Tool Count3/5
A single tool is borderline for the server's purpose. While it may be sufficient for a very narrow focus, it feels thin compared to typical MCP servers.
Completeness4/5
The tool covers the core functionality of checking package safety for npm and PyPI. Minor gaps exist (e.g., no support for other ecosystems or additional actions), but agents can work with what's provided.
Available Tools
1 toolcheck_package_safetyBInspect
Check whether an npm or PyPI package is safe to install. Costs $0.005 USDC via x402 per call.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Exact package name to check for safety before installing | |
| ecosystem | Yes | Package ecosystem to check |
Tool Definition Quality
B3.4/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full responsibility for behavioral disclosure. It mentions the cost mechanism, which is valuable, but does not disclose what happens when a package is unsafe (e.g., return type, possible errors) or any side effects. The core behavior is stated, but depth is lacking.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with 18 words, highly concise. It front-loads the core purpose and adds the cost detail efficiently. However, it could benefit from slight restructuring for clarity (e.g., separating cost info).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 parameters, no output schema, no siblings), the description covers the essential purpose and cost but fails to describe the return value or possible outputs. With no output schema, the agent would benefit from knowing the response format. The description is functionally complete for a basic check but leaves an important gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%: both 'name' and 'ecosystem' have descriptions. The tool description only adds cost context, not parameter details, so it does not meaningfully augment the schema. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description states exactly what the tool does: 'Check whether an npm or PyPI package is safe to install.' The verb 'check' and resource 'package safety' are specific, and the ecosystems npm and PyPI are clearly mentioned. No siblings exist, so differentiation is not needed.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives or when not to use it. It only mentions a cost of $0.005 USDC via x402 per call, which is a constraint but not usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
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For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
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For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
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