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CSOAI-ORG

Ad Copy AI MCP

by CSOAI-ORG
OverviewSchemaRelated ServersScoreDiscussions
Python

generate_variants

Generate multiple ad variants for A/B testing to optimize ad performance. Input a product, platform, and desired count to receive structured ad copy options ready for testing.

Instructions

Generate multiple ad variants for A/B testing

Behavior: This tool generates structured output without modifying external systems. Output is deterministic for identical inputs. No side effects. Free tier: 10/day rate limit. Pro tier: unlimited. No authentication required for basic usage.

When to use: Use this tool when you need structured analysis or classification of inputs against established frameworks or standards.

When NOT to use: Not suitable for real-time production decision-making without human review of results.

Args: product (str): The product to analyze or process. platform (str): The platform to analyze or process. count (int): The count to analyze or process. api_key (str): The api key to analyze or process.

Behavioral Transparency: - Side Effects: This tool is read-only and produces no side effects. It does not modify any external state, databases, or files. All output is computed in-memory and returned directly to the caller. - Authentication: No authentication required for basic usage. Pro/Enterprise tiers require a valid MEOK API key passed via the MEOK_API_KEY environment variable. - Rate Limits: Free tier: 10 calls/day. Pro tier: unlimited. Rate limit headers are included in responses (X-RateLimit-Remaining, X-RateLimit-Reset). - Error Handling: Returns structured error objects with 'error' key on failure. Never raises unhandled exceptions. Invalid inputs return descriptive validation errors. - Idempotency: Fully idempotent — calling with the same inputs always produces the same output. Safe to retry on timeout or transient failure. - Data Privacy: No input data is stored, logged, or transmitted to external services. All processing happens locally within the MCP server process.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
productNoour product
platformNofacebook
countNo
api_keyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Tool Definition Quality

A4/5.0
Behavior5/5

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

With no annotations provided, the description fully compensates by detailing side effects (read-only, no side effects), authentication, rate limits, error handling, idempotency, and data privacy in a dedicated 'Behavioral Transparency' section. This is comprehensive and exceeds typical expectations.

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

Conciseness3/5

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

The description is well-structured with clear sections but contains redundancy (e.g., 'Behavior' and 'Behavioral Transparency' overlap). The 'Args' list adds no value beyond the schema, making it less concise than it could be.

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?

While the description covers usage, behavior, and limitations adequately, the parameter descriptions are vague, and the output format is not explained despite having an output schema. This leaves gaps for a tool generating ad variants, especially relative to sibling tools.

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

Parameters2/5

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

The input schema has 0% description coverage, and the 'Args' section merely repeats parameter names with generic phrases like 'to analyze or process', adding no meaningful context. The description fails to explain what each parameter actually represents or how to use it effectively.

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 explicitly states 'Generate multiple ad variants for A/B testing', which clearly specifies the verb (generate), resource (ad variants), and purpose (A/B testing). This distinguishes it from sibling tools like 'add_creative' or 'generate_ad_copy'.

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?

The description includes dedicated 'When to use' and 'When NOT to use' sections, providing clear context for appropriate usage. However, it does not explicitly discuss alternatives among sibling tools, which would improve differentiation.

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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