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CSOAI-ORG

Marketing Analytics AI MCP

by CSOAI-ORG
OverviewSchemaRelated ServersScoreDiscussions
Python

ad_copy_generator

Generate ad copy variants tailored to any platform with proper character limits and best practices. Tailor tone, audience, and call to action to improve campaign performance.

Instructions

Generate ad copy variants tailored to a specific platform with proper character limits and best practices.

Args: product: Product or service name audience: Target audience description platform: Ad platform (google_search, facebook, instagram, linkedin, twitter, tiktok) tone: Copy tone (professional, casual, urgent, inspirational, humorous) cta: Call to action text (default: auto-generated based on tone)

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. 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
ctaNo
toneNoprofessional
api_keyNo
productYes
audienceYes
platformNofacebook

Tool Definition Quality

A4/5.0
Behavior5/5

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

No annotations provided, so the description fully covers behavioral traits. It details side effects (read-only, no modifications), authentication (no auth for basic, API key for pro), rate limits (10/day free, unlimited pro), error handling (structured errors), idempotency, and data privacy. This exceeds expectations.

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 well-structured with sections for args, behavior, when to use, and behavioral transparency. However, it is somewhat verbose with redundancy (e.g., 'Behavior' section then repeated in 'Behavioral Transparency'). Could be condensed without losing value.

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?

Given 6 parameters and no output schema, the description covers behavioral context well but lacks details on the output format or structure. The 'structured output' is not defined, leaving the agent uncertain about return types. Generic 'when to use' section also misses tool-specific context.

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 0%, so the description must compensate. It lists parameters but adds only minimal detail (e.g., defaults for tone, platform, cta). It does not explain allowed values for 'platform' or 'tone' beyond examples, nor does it describe the 'api_key' parameter. Names are self-explanatory, but more specifics would improve semantics.

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 'Generate ad copy variants tailored to a specific platform with proper character limits and best practices.' It specifies the action (generate), the output (ad copy variants), and constraints (platform-specific). The tool is distinct from siblings like ab_test_analyze or attribution_model.

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 'When to use' section is generic and not specific to ad copy generation (e.g., 'structured analysis or classification'). It lacks explicit guidance on when to choose this tool over alternatives or what prerequisites are needed (e.g., target platform knowledge). The 'When NOT to use' is helpful but brief.

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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