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Glama

Security Intel MCP

by com.datakoot

package_vulnerabilities

List known vulnerabilities for a software package (optionally a specific version) via OSV. Ecosystems: npm, pypi, cargo, go, maven, rubygems, nuget, composer, pub, hex.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesExact package name as published in that registry, e.g. lodash for npm, requests for pypi.
versionNoOptional; if given, only vulns affecting that version are returned
ecosystemYesPackage registry to look in. One of: npm, pypi, cargo, go, maven, rubygems, nuget, composer, pub, hex.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses useful behavioral context: the data source is OSV, version filtering is optional, and only the listed ecosystems are supported. Since there are no annotations, the description carries the transparency burden, but it omits details such as the shape of the returned vulnerability list, empty-result behavior, and any access or rate-limit considerations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two tight sentences with the core action front-loaded and the ecosystem list appended compactly. There is no filler, repetition, or unnecessary detail, making it easy for an agent to parse quickly.

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?

For a simple three-parameter read tool, the description is mostly sufficient to invoke the tool correctly. However, there is no output schema and the description does not explain what fields the vulnerability results contain, nor does it route the agent away from sibling tools when the context is a dependency audit or a CVE lookup.

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%, so the schema already documents name, version, and ecosystem. The description adds a succinct restatement of the optional version and supported ecosystems, but it does not add significant meaning beyond what the input schema already provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb, 'List', and identifies a concrete resource: known vulnerabilities for a software package, optionally filtered by version, via OSV. It is distinct from the sibling tools because it is scoped to a package/ecosystem lookup, but it does not explicitly compare itself with audit_dependencies or cve_lookup.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool's use case: call it when you need OSV vulnerability data for a named package in a supported ecosystem. However, it gives no explicit guidance about when to prefer the sibling tools instead, such as using cve_lookup for CVE IDs or audit_dependencies for dependency-tree auditing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.7/5.0
Disambiguation4/5

The three tools serve distinct purposes: bulk manifest scanning, per-package vulnerability listing, and specific CVE details. audit_dependencies and package_vulnerabilities overlap in domain but differ in input granularity (manifest vs. single package), so misselection is unlikely with clear descriptions.

Naming Consistency3/5

Names use lowercase with underscores, but the pattern varies: 'audit_dependencies' is verb_noun, 'cve_lookup' is noun_verb, and 'package_vulnerabilities' is noun_noun. There is no consistent verb-first or object-first convention, though the names remain readable and conventional for security tools.

Tool Count4/5

With three tools, the server is on the lean side but still covers core vulnerability intelligence workflows. The count feels slightly thin for a 'Security Intel' scope, yet each tool addresses a substantial use case without unnecessary bloat.

Completeness4/5

The set covers bulk dependency auditing, package-level vulnerability queries, and CVE lookup, which are essential functions for security intelligence. Minor gaps exist, such as no search-by-keyword tool or advisory feed, but the main workflows for checking known vulnerabilities are well covered.

Resources