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Ansvar-Systems

Security Controls MCP Server

search_controls

Search for security controls by keyword across 1,451 SCF controls. Returns matching controls with text snippets and framework mappings. Optionally filter to specific frameworks.

Instructions

Full-text search across all 1,451 SCF controls by keyword in name or description. Returns matching controls with text snippets and their top framework mappings. Use this to discover controls by topic (e.g., 'encryption', 'incident response', 'access control'). Optionally filter to controls that map to specific frameworks. Returns 'No controls found' when no matches exist. Each result is ~100 tokens; default limit of 10 returns ~1000 tokens.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch keyword or phrase. Matches against control names and descriptions. Examples: 'encryption', 'access control', 'incident response', 'data classification'. Must not be empty.
frameworksNoOptional: filter results to controls that map to these framework keys (e.g., ['iso_27001_2022', 'nist_csf_2.0']). Use list_frameworks to discover valid keys.
limitNoMaximum number of results to return. Default: 10. Use lower values to save tokens.
Behavior4/5

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

No annotations provided, so description carries burden. Discloses return format (text snippets, top framework mappings), token size per result, default limit and total tokens, and 'No controls found' response. Informs token economy. Doesn't discuss rate limits or authentication, but acceptable for a search tool.

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?

Four well-structured sentences, front-loaded with core functionality. Information dense without unnecessary words. Every sentence serves a purpose: action, return, use case, token estimate.

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?

Tool is simple search with one required param. Description covers search scope, return content, filtering, error case, and token budget. Missing details on pagination or query syntax (exact phrase, case sensitivity), but adequate for typical agent use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%. Adds value with examples for query, explanation of frameworks parameter referencing list_frameworks, and clarification of limit's token-saving purpose. Goes beyond schema by providing usage hints.

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?

The description clearly states the tool performs full-text search across all SCF controls by keyword, returning matching controls with snippets and framework mappings. It distinguishes from sibling tools like get_control (single control retrieval) and get_framework_controls (list by framework).

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

Usage Guidelines4/5

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

Provides explicit use case: 'discover controls by topic' with examples. Mentions optional filtering to specific frameworks and suggests using list_frameworks for valid keys. Lacks explicit 'when not to use' or direct comparison to alternatives, but context is clear.

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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