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AlexandreCalvet

Ogury MCP Server

by AlexandreCalvet
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TypeScript
Remote

Server Quality Checklist

42%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation2/5

    The two tools have overlapping purposes, as both retrieve campaign performance data, which could cause confusion for an agent. While 'get_campaign_details' targets a specific campaign by ID and 'get_campaigns_report' offers flexible filtering, the descriptions do not clearly differentiate their use cases, leading to potential misselection.

    Naming Consistency5/5

    The tool names follow a consistent verb_noun pattern with 'get_campaign_details' and 'get_campaigns_report', both using snake_case and starting with 'get'. This predictability makes it easy for agents to understand the naming convention.

    Tool Count2/5

    With only 2 tools, the server feels thin and under-scoped for a campaign management domain, as it lacks essential operations like creating, updating, or deleting campaigns. This limited set may hinder agent workflows and suggests an incomplete implementation.

    Completeness2/5

    The tool surface is severely incomplete for campaign management, covering only read operations (details and reports) without any create, update, or delete capabilities. This creates significant gaps that will likely cause agent failures in handling full campaign lifecycles.

  • Average 2.8/5 across 2 of 2 tools scored.

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

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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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the action ('Get') and mentions 'flexible filtering', but doesn't cover critical aspects like whether this is a read-only operation, potential rate limits, authentication requirements, or what the output format looks like. For a tool with 8 parameters and no annotations, this is insufficient.

    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, efficient sentence that gets straight to the point without unnecessary words. It's appropriately sized for the tool's complexity, though it could be more informative while maintaining 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 tool's complexity (8 parameters, no output schema, no annotations), the description is inadequate. It doesn't explain what a 'performance report' entails, how filtering works, or what the return values are. For a reporting tool with multiple identifiers and no structured output, more context is needed to guide the agent effectively.

    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?

    The description adds minimal value beyond the input schema, which has 100% coverage with clear parameter descriptions. The phrase 'flexible filtering' hints at the filtering capability of the parameters but doesn't explain how they interact or provide additional context about the identifiers. With high schema coverage, the baseline score of 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 the tool 'Get campaign performance report with flexible filtering', which provides a clear verb ('Get') and resource ('campaign performance report'). However, it's somewhat vague about what constitutes 'performance report' and doesn't distinguish it from the sibling tool 'get_campaign_details', leaving ambiguity about their 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 Guidelines2/5

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

    The description mentions 'flexible filtering' but provides no guidance on when to use this tool versus the sibling 'get_campaign_details'. There's no mention of alternatives, prerequisites, or specific contexts where this tool is preferred, leaving the agent without usage direction.

    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 provided, the description carries the full burden of behavioral disclosure. It states a read operation ('Get'), implying it's likely non-destructive, but doesn't cover aspects like authentication needs, rate limits, error handling, or what 'performance details' entail. This leaves significant gaps for an agent to understand the tool's behavior.

    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, direct sentence with no wasted words, clearly front-loading the core action. It is appropriately sized for the tool's complexity, making it efficient and easy to parse.

    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 has 5 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain the return values (e.g., what 'performance details' include), behavioral traits, or usage context, leaving the agent with incomplete information for proper invocation.

    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?

    The schema description coverage is 100%, meaning all parameters are documented in the input schema. The description adds no additional parameter semantics beyond implying 'campaignId' is key, so it meets the baseline of 3 without compensating for any gaps.

    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 verb ('Get') and resource ('campaign performance details') with a specific identifier ('by campaign ID'), making the purpose understandable. However, it doesn't explicitly differentiate from the sibling tool 'get_campaigns_report', which might be a broader report vs. specific details, leaving some ambiguity.

    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?

    The description provides no guidance on when to use this tool versus the sibling 'get_campaigns_report', nor does it mention any prerequisites or alternative contexts. It lacks explicit usage instructions, relying solely on the implied action.

    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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