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ClayYTsai

agent-discovery-mcp

by ClayYTsai
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool serves a clearly distinct function: searching agents by skill, retrieving a detailed card, and calling an agent with payment. No overlap in purpose.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case (call_agent_with_payment, find_agents_by_skill, get_agent_card), making them predictable.

    Tool Count4/5

    With 3 tools, the set is minimal but well-scoped for the server's purpose of discovery and basic interaction. Each tool earns its place, though a few more could be justified.

    Completeness4/5

    Core functionalities (search, details, call) are covered. Minor gaps exist, such as listing all agents without a skill filter or managing registrations, but agents can work around these.

  • Average 4.1/5 across 3 of 3 tools scored.

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

    • 1 of 3 community issues answered or closed 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 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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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?

    No annotations are provided, so the description carries full burden. It does not disclose behavioral traits such as whether the tool is read-only, what happens if the agent_id is invalid, or if any authentication is required. It only repeats the purpose.

    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 with 15 words, front-loaded with the main action and resource. Every word adds value; no redundancy or filler.

    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?

    The description covers the tool's purpose but lacks details on return format, error handling, or edge cases (e.g., nonexistent agent). Given no output schema and simple parameters, it is adequate but could be more complete by stating that it returns the full card object.

    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 100% with each parameter already described (agent_id: ERC-8004 token ID; chain_id: Chain ID). The description adds no new meaning beyond the schema, so it meets the baseline of 3.

    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 ('Fetch'), the resource ('single agent's full ERC-8004 registration card'), and lists specific contents (name, description, services, x402 support, trust models). It distinguishes from sibling tools like 'call_agent_with_payment' and 'find_agents_by_skill' by focusing on fetching a single agent's detailed card.

    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 when to use this tool (to fetch a single agent's details), but it does not explicitly state when not to use it or suggest alternatives. For example, it could mention that for searching by skill, one should use 'find_agents_by_skill', but it does not.

    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, so description carries full burden. Discloses automatic retry on 402, use of Coinbase SDK and EOA wallet from env var, and max payment limit. Could mention side effects (cost) and error handling, but current level is good.

    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 efficient sentences front-load key purpose and behavior. No unnecessary words; every sentence adds value.

    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?

    No output schema; description does not specify return value (likely HTTP response). Missing error handling details and prerequisites. Incomplete for a complex payment tool.

    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 coverage is 100% with clear descriptions for all 4 parameters. The description does not add extra meaning beyond the schema; baseline 3 is appropriate.

    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?

    Clearly states the tool calls an agent HTTP endpoint with automatic x402 payment. Distinct from siblings (find_agents_by_skill, get_agent_card) which are about searching and retrieving agent info, not making paid calls.

    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?

    Implicitly clear: use when you need to call an agent endpoint that may require payment. No explicit exclusions or alternatives, but context is sufficient for typical use.

    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 must fully disclose behavior. It specifies the tool is a search operation that returns a limited set of candidates with specific fields, and mentions the use of a public API. It implies read-only behavior. It could be more explicit about being a read operation, but it's adequate.

    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 two sentences, no unnecessary words, and front-loads the key action and source. Every sentence 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 simple search tool with 4 parameters and no output schema or annotations, the description covers the purpose, scope, and return fields completely. It provides enough context for an agent to use the tool effectively.

    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?

    Schema description coverage is 100%, so the baseline is 3. The description adds value by explaining the return fields (id, chain, name, description, endpoint, x402 support flag) and clarifying how `limit` and `x402_only` relate to the response, compensating for the lack of an output schema.

    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 verb 'Search' and the resource 'ERC-8008 registry for agents matching a skill keyword.' It distinguishes from siblings `call_agent_with_payment` and `get_agent_card`, which serve different purposes (calling and retrieving cards).

    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 implies usage for finding agents by skill, which is straightforward. While it does not explicitly state when not to use it or provide alternatives, the context is clear enough for an AI agent to decide when to invoke it.

    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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