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CallMarcus

SecurityScorecard MCP Server

by CallMarcus
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

Security Data Query

query_security_data

Query SecurityScorecard API endpoints with validation, alternative suggestions, and parameter hints to retrieve security metrics and risk data.

Instructions

Direct API access with smart endpoint validation. Uses API discovery to validate endpoints, suggest alternatives, and provide parameter hints.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainNoDomain to use in endpointexample.com
methodNoHTTP methodGET
endpointYesAPI endpoint to query (e.g., /companies/{domain}/factors)
fetch_allNoFollow pagination and return every page of a GET list endpoint (capped at 20 pages; a truncation notice is added if the cap is hit)
validate_onlyNoOnly validate endpoint without calling API

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv2.0.0
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • addedInput schema / properties / fetch_all
      Added value: +{
+  "default": false,
+  "description": "Follow pagination and return every page of a GET list endpoint (capped at 20 pages; a truncation notice is added if the cap is hit)",
+  "type": "boolean"
+}
  2. First observedv1.1.1

TDQS

C2.6/5.0
Behavior2/5

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

With no annotations, the description carries the full burden but discloses only endpoint validation and parameter hints. It omits critical behavioral traits: authentication requirements, side effects of POST/PUT/DELETE, rate limits, error behavior, and whether calls are read-only or destructive.

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 two front-loaded sentences with no filler, efficiently stating the core mechanism and validation features. It is appropriately sized for a short summary, though the first sentence is vague rather than wasteful.

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

Completeness2/5

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

This is a complex tool with five parameters, no annotations, and no output schema, yet the description omits essential context: what security data is queried, how authentication works, what happens with mutating methods, and what the return format looks like. It is not complete enough for an agent to invoke confidently.

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 all five parameters thoroughly. The description adds only a generic 'parameter hints' phrase, which does not extend parameter meaning beyond the schema; baseline 3 is appropriate.

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

Purpose3/5

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

The description states 'Direct API access with smart endpoint validation,' which gives a general verb-and-mechanism but does not specify the resource (security data) or distinguish this tool from siblings like api_discovery. An agent can infer it performs API calls, but the actual purpose is vague.

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?

There is no explicit guidance on when to use this tool versus alternatives such as api_discovery or validate_data_completeness. The description only mentions behavior ('Uses API discovery to validate endpoints'), not usage conditions or exclusions.

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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