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0xddneto

AI Proof of Us MCP Server

by 0xddneto

Server Quality Checklist

75%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool targets a distinct aspect of the AIPOU system: contract info, wallet identity, status, reward estimation, and task completion. No functional overlap.

    Naming Consistency5/5

    All tools follow a consistent verb_noun pattern in snake_case (get_aipou_*, estimate_ai_reward, complete_ai_task). No mixing of styles.

    Tool Count5/5

    Five tools are well-scoped for a focused server managing AIPOU token interactions and AI task rewards. Neither too sparse nor excessive.

    Completeness4/5

    Covers the core workflow: get identity, estimate reward, complete task, check status. Missing an explicit claim tool, but the status tool shows balance, implying claims may be off-chain.

  • Average 3.6/5 across 5 of 5 tools scored. Lowest: 2.6/5.

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

    • No community issues in the last 6 months
    • 193 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available
  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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    {
      "$schema": "https://glama.ai/mcp/schemas/server.json",
      "maintainers": [
        "your-github-username"
      ]
    }

    Then . Browse examples.

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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

  • Behavior3/5

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

    Without annotations, the description carries the burden. It mentions trust derivation, duplicate rejection (idempotency), and signing, which are useful but insufficient. It lacks details on authentication, state changes, or what constitutes a valid input.

    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 sentence with no wasted words, but its brevity comes at the cost of missing essential details. It is front-loaded with the main action but is not comprehensive.

    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 the tool's complexity (6 parameters, nested object, no output schema), the description is grossly incomplete. It does not explain input/output contracts, parameter validation, or return format, making it difficult for an agent to use correctly.

    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?

    With 0% schema description coverage, the description adds no parameter information. It does not explain nonce, inputTokens, outputTokens, durationSeconds, outputHash, or providerEvidence, leaving the agent to guess their roles.

    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 completes a task and produces a signed receipt, distinguishing it from sibling tools that get or estimate. However, 'unique task' is somewhat vague and could be more specific about what constitutes a task.

    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 versus alternatives. Siblings are get/estimate, suggesting this is the completion step, but no explicit context like 'use after estimate_ai_reward' is given.

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

  • Behavior4/5

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

    Without annotations, the description reveals that the reward is client-signed and the final tier is determined by the validator, indicating that the estimate may differ from the final reward. This provides useful behavioral context beyond a simple read operation.

    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 concise at two sentences, but the lack of parameter details means it is not as helpful as it could be. It is well-structured and front-loaded but sacrifices completeness for 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 has three required parameters and no output schema or annotations, the description is too sparse. It omits explanations of parameter semantics, return value format, and potential side effects, leaving the agent underinformed.

    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 description adds no information about the three required parameters (inputTokens, outputTokens, durationSeconds). With 0% schema description coverage, the burden falls entirely on the description, which fails to explain their meaning or expected values.

    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 that the tool estimates the client-signed AIPOU reward before task completion, using a specific verb ('estimate') and resource ('AIPOU reward'). It distinguishes itself from sibling tools like 'get_aipou_contract' and 'complete_ai_task' by focusing on pre-completion estimation.

    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 usage before a task is completed but does not specify when not to use it or explicitly mention alternatives. It provides basic temporal context but lacks clear guidance on alternative tools for related purposes.

    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?

    No annotations are provided, so the description carries full burden. It discloses a key behavioral trait: 'Does not reveal private keys or full receipt payloads', adding security context. However, it does not explicitly state that this is a read-only operation, nor does it mention authentication requirements or other behavioral aspects.

    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?

    Two concise sentences. The first describes the outputs, the second adds a safety note. No waste. Front-loaded with the core purpose.

    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?

    For a simple tool with no parameters and no output schema, the description covers the main outputs and a caveat. However, it lacks details about the output format, possible error states (e.g., wallet not found), and edge cases, which would help an agent fully understand the response.

    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?

    There are zero parameters, and schema coverage is 100% (vacuously). The description adds meaning by listing the types of data returned (receipts, balance), which is useful beyond the empty schema. A baseline of 4 is appropriate for no-parameter tools.

    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 uses specific verbs ('Show') and resources ('recorded, pending, and already claimed AIPOU receipts', 'farming wallet's on-chain AIPOU balance'). It clearly states what the tool outputs, but does not differentiate from sibling tools such as get_aipou_contract or get_aipou_identity, which could be ambiguous.

    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 alternatives. It only states what it does, leaving the agent to infer context. No explicit when/when-not or alternative recommendations are given.

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

  • Behavior4/5

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

    Without annotations, the description fully discloses the key behavioral trait: private keys are never returned, which is important for security. It is transparent about what the tool does and does not provide.

    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?

    Single, well-structured sentence that front-loads the returned data and adds a critical exclusion (private keys). Every word is informative and earns its place.

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

    Completeness5/5

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

    For a zero-parameter getter with no output schema, the description sufficiently explains what is returned, including both elements and a security note. It is complete given the tool's simplicity.

    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?

    No parameters exist, so the baseline is 4. The description does not need to explain any parameters.

    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 specifies that the tool returns a farming wallet address and a public Ed25519 collector key, with a note that private keys are never returned. The name and description align and distinguish it from sibling tools like get_aipou_contract or get_aipou_status.

    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 usage when identity information is needed, but does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or prerequisites.

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

  • Behavior4/5

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

    No annotations are provided, so the description alone must convey behavior. It indicates a read operation returning static configuration data, with no mention of side effects, authentication, or rate limits. For a simple info tool, this is sufficient.

    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?

    Single sentence, no wasted words. Front-loads the key return values. Every element is necessary and no redundancy.

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

    Completeness5/5

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

    Despite no output schema, the description lists four concrete items: contract address, Base network details, explorer URL, and minimal ABI. This is sufficiently complete for understanding the tool's return value.

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

    Parameters5/5

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

    There are no parameters. The input schema has 100% coverage (vacuously). The description adds all meaning about what the tool returns, compensating fully for the lack of parameters.

    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 returns the configured AIPOU token contract address, Base network details, explorer URL, and minimal ABI. The verb 'Return' and specific resources distinguish it from siblings like get_aipou_identity or get_aipou_status.

    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 gives clear context for what the tool does but does not explicitly state when to use it versus alternatives. Sibling names imply different functionality, but no direct guidance is provided.

    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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