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@guardbee/mcp-security-proxy

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mcp_config_auditor__scan_config_text

Scan MCP client config JSON to detect unpinned packages, exposed secrets, wildcard auto-approve, unauthenticated remote endpoints, and typosquats before deploying.

Instructions

Scan an MCP client config JSON string (Cursor mcp.json, Claude Desktop, Windsurf, or VS Code) for unpinned packages, secrets, wildcard auto-approve, unauthenticated remote endpoints, and typosquats.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
labelNoOptional filename shown in findings
contentYesRaw JSON config

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.1

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It usefully discloses the detection taxonomy the agent will get back, and 'Scan ... for' strongly implies a non-destructive read. However it says nothing about whether the content is executed, network access, auth needs, or result shape, leaving real behavioral gaps for an unaided tool.

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?

One front-loaded sentence with the verb and input first and the check list after. Every listed item (unpinned packages, secrets, wildcard auto-approve, unauthenticated endpoints, typosquats) earns its place as distinct scope information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, so the enumerated detection categories usefully stand in for describing what findings are produced. With no annotations and a trivial two-parameter schema, the description is nearly sufficient; only return format, severity, and pagination are left unspecified.

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 both 'label' and 'content' are already documented. The description's 'JSON string' phrasing loosely corroborates the content parameter but adds no format, size, or parsing constraints beyond the schema. Baseline 3 applies when the schema does the heavy lifting.

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?

States a specific verb (scan) and resource (an MCP client config JSON string), naming the concrete client formats it accepts (Cursor mcp.json, Claude Desktop, Windsurf, VS Code) and enumerating the defect classes it targets. The 'JSON string' input hint implicitly separates it from the sibling scan_file/scan_directory tools without needing to open a schema.

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 list of detection categories implies when the tool is useful (auditing MCP client configs), but there is no explicit when-to-use statement, no prerequisites, and no routing to alternatives such as scan_file for a path or scan_directory for a tree. Usage is inferable but not stated.

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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