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Mohit4022-cloud

Marketing Automation MCP Server

Server Quality Checklist

58%
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  • Latest release: v1.1.0

  • Disambiguation5/5

    Each tool targets a distinct marketing function: audience analysis, copy creation, reporting, and budget optimization. There is no overlap in purpose.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern (analyze_*, create_*, generate_*, optimize_*), making them predictable and easy to distinguish.

    Tool Count4/5

    With 4 tools, the set is slightly lean but covers core marketing automation tasks. It does not feel overly sparse or bloated for a focused server.

    Completeness3/5

    The tools cover analysis, copy, reporting, and optimization, but lack common features like campaign lifecycle management (create, schedule, pause) or list/segment management, leaving notable gaps.

  • Average 2.8/5 across 4 of 4 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 0 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing
  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior2/5

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

    No annotations are provided, and the description fails to disclose behavioral traits such as read/write nature, side effects, or mode implications. 'Deterministic demo mode' hints at reproducibility but is not explained.

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

    Conciseness2/5

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

    The description is a single sentence, but it is under-specified rather than concise. It omits critical details that would justify its brevity.

    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?

    With 6 parameters, no annotations, and no explanation of the output schema, the description is insufficient for an agent to correctly invoke the tool. The live-mode vs. demo distinction is mentioned but not fleshed out.

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

    Parameters1/5

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

    The input schema has 0% description coverage for its 6 parameters, and the description does not mention or clarify any parameters. It adds no value beyond the schema's field names.

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

    Purpose4/5

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

    The description clearly states the tool analyzes audience segments and mentions two modes (deterministic demo vs. live), which distinguishes it from sibling tools like create_campaign_copy or generate_campaign_report. However, it lacks specificity on what the analysis produces.

    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?

    No guidance on when to use this tool versus alternatives; no prerequisites or context for the modes. The description only states the action without any conditional advice.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior2/5

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

    With no annotations, the description must disclose behavioral traits. It only states the high-level purpose but omits details like budget modification being destructive, required permissions, or impact of reallocation. Minimal transparency.

    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 a single 10-word sentence, concise but too brief for a tool with 6 parameters. It front-loads the action but lacks essential context, making it minimally adequate.

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

    Completeness1/5

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

    Given 6 parameters, no schema descriptions, no annotations, and an output schema not explained, the description is severely incomplete. An agent cannot infer inputs, outputs, or behavioral effects from this alone.

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

    Parameters1/5

    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 does not mention any parameters (campaign_ids, total_budget, etc.) nor explain their meaning. Only the optimization_goal enum is partially documented in the schema itself.

    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 action (reallocate campaign budget) and the method (live platform metrics, optimization logic). It distinguishes from siblings like analyze_audience_segments or create_campaign_copy, which are unrelated.

    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?

    No guidance on when to use this tool versus alternatives (e.g., when to manually adjust budgets). No exclusions or prerequisites are mentioned.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior3/5

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

    The description discloses that the tool can use live data or a deterministic demo mode, which is a behavioral trait. However, with no annotations, it fails to disclose other important aspects like permissions, side effects, or rate limits.

    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 a single, front-loaded sentence that efficiently conveys the core action. It is concise, though it could briefly describe parameters without losing brevity.

    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?

    Given the complexity (6 parameters, nested objects, enums), the description is too sparse. It does not explain demo mode, report formats, or group_by behavior. Output schema exists but does not justify the lack of parameter context.

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

    Parameters1/5

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

    The input schema has 0% description coverage and the tool description provides no explanations for any of the 6 parameters, including required ones like campaign_ids, date_range, and metrics. This forces the agent to infer meaning from schemas alone.

    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 generates campaign performance reports and distinguishes it from siblings by specifying data sources (live vs demo mode). The verb 'generate' and resource 'campaign performance reports' are specific and unambiguous.

    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?

    No guidance is provided on when to use this tool vs alternatives like analyze_audience_segments. There is no mention of prerequisites or exclusion criteria.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior2/5

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

    No annotations are provided, so the description must carry the full burden of behavioral disclosure. It mentions two modes (AI provider and deterministic demo) but fails to disclose potential side effects, failure modes, authentication requirements, rate limits, or any constraints. This is a significant gap for a tool with no annotations.

    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?

    The description is a single sentence that efficiently communicates the core purpose and key behavioral distinction (two modes). There is no fluff; every word earns its place. The structure effectively front-loads the essential information.

    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?

    Given the tool's complexity (9 parameters, 5 required) and the lack of schema descriptions and annotations, the description should provide more contextual guidance. Although an output schema exists (so return values need no explanation), the lack of parameter semantics and behavioral detail makes the description incomplete for an agent to use the tool confidently.

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

    Parameters1/5

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

    The input schema has 0% description coverage, meaning no parameter documentation exists in the schema. The tool description does not provide any additional meaning for the 9 parameters (e.g., expected formats, examples, or relationships). The only hint comes from parameter titles, which is insufficient for correct invocation.

    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 action ('generate'), the resource ('campaign copy variants'), and the two operational modes (AI provider or deterministic demo mode). It distinguishes well from sibling tools like analyze_audience_segments, generate_campaign_report, and optimize_campaign_budget, which serve different purposes.

    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 description implies the tool is for generating copy, but it does not explicitly state when to use it versus alternatives. There is no guidance on prerequisites, exclusions, or conditions that would help an agent decide between this tool and others. The context suggests usage, but explicit guidelines are missing.

    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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