Audit a whole dependency manifest for known vulnerabilities in one call. Paste a package.json (as 'manifest'), or pass a 'dependencies' array of {name, version} objects. Returns per-package findings and a summary. Ecosystem defaults to npm.
| Name | Required | Description | Default |
|---|---|---|---|
| manifest | No | Raw package.json contents | |
| ecosystem | No | Default npm | |
| dependencies | No | [{name, version}] entries |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden and does disclose meaningful behavior: it accepts a raw package.json or a dependencies array, returns per-package findings plus a summary, and defaults the ecosystem to npm. It does not cover edge-case behavior like what happens if both inputs are supplied or if the manifest is invalid, but the core behavior is transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences cover purpose, input modes, return behavior, and default ecosystem without repetition. The most important purpose statement is front-loaded, and every sentence contributes meaningful information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description gives a solid high-level picture but leaves gaps: there is no output schema, and the return value is only described as 'per-package findings and a summary' with no detail on structure, severities, or counts. It also does not address ambiguous inputs, such as supplying both manifest and dependencies, or how errors like an invalid package.json manifest are handled.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3, but the description adds real value by clarifying that manifest and dependencies are alternative input modes rather than independent optional fields. It also contextualizes the ecosystem parameter by stating the npm default, which is not inferable from the raw schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Audit a whole dependency manifest for known vulnerabilities in one call.' This clearly states what the tool does and its batch-oriented scope, but it does not explicitly differentiate it from the sibling tools cve_lookup or package_vulnerabilities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'in one call' and 'whole dependency manifest' imply this is for bulk manifest auditing, and the description explains how to provide input via manifest or dependencies. However, it never states when to prefer this tool over cve_lookup or package_vulnerabilities, nor does it mention any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.