LEGIT
Server Details
Trust scores and organic demand intelligence for x402 agents: measured merchant behavior across 20 chains, a free leaderboard, and per-call USDC verdicts on Algorand and Base. Created by GONNA.
- Status
- Healthy
- Uptime
- 100.0% over 41 days
- Last Tested
- Transport
- Streamable HTTP · MCP 2024-11-05
- URL
TDQS
Scored across 4 tools
Each tool has a clearly distinct purpose: checking a single merchant, comparing merchants, generating a badge, and viewing a leaderboard. No overlap or ambiguity exists between them.
The first three tools follow verb_noun convention (check_trust, compare_merchants, get_badge_url), but 'leaderboard' is a noun-only exception. Minor deviation, but overall predictable.
With only 4 tools, the set is tightly scoped to the server's purpose of providing trust scores and comparisons. Each tool earns its place, and the small count is a strength for clarity.
The domain is merchant trust evaluation and display. The toolset covers all apparent needs: individual trust reports, head-to-head comparison, embeddable badges, and network-filtered leaderboard. No obvious gaps.
Available Tools
4 toolscheck_trustAInspect
Trust report for one merchant: 0-100 score, letter grade, uptime, median latency and a plain-English explanation. Accepts Algorand, EVM or Solana addresses, or an https URL.
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | Merchant address (Algorand / EVM / Solana) or https URL |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the exact output contents (score, grade, uptime, latency, explanation) and input formats, giving a solid account of behavior. However, it does not mention potential error handling or response format, though these are not critical for a simple read-only lookup.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences. The first sentence front-loads the purpose and output details, while the second specifies input types. Every word contributes useful information, with no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter tool with no output schema, the description provides a complete picture: what it does, what it returns (specific metrics), and what inputs it accepts. It is sufficient for an agent to select and invoke the tool correctly without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description already covers the parameter fully (100% coverage), stating the supported address formats. The tool description adds minimal new meaning—it essentially restates the same formats ('Algorand, EVM or Solana addresses, or an https URL') without additional syntax or usage details. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool produces a 'trust report' for a single merchant, specifying the output metrics (0-100 score, letter grade, uptime, median latency, explanation). This distinguishes it from siblings like 'compare_merchants' (comparison) and 'leaderboard' (ranking), making its purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for a single merchant lookup with 'for one merchant' and lists accepted input types, but does not explicitly contrast with sibling tools or mention when not to use it. The context is clear enough for selection, but lacks explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
compare_merchantsAInspect
Head-to-head trust comparison of 2-5 merchant addresses. Returns the winner address and a one-sentence rationale.
| Name | Required | Description | Default |
|---|---|---|---|
| addresses | Yes | 2-5 merchant addresses to compare |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosing behavior. It states the input (2-5 addresses) and output (winner + rationale), which is useful. However, it does not disclose tie-breaking logic, how trust is computed, error handling, or whether the operation is read-only. Given the absence of annotations, this is a moderate gap, so a score of 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that states the core function and expected output. Every phrase adds value—'head-to-head', '2-5', 'winner address', and 'one-sentence rationale' are all informative. There is no superfluous content, making it highly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description provides enough context for an agent to invoke it correctly: what to pass (addresses), the count constraints, and what to expect back (winner + rationale). It leaves out minor edge-case behaviors (ties, invalid addresses), but these are not critical for basic usage given the tool's simplicity. The sibling context also helps set expectations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers 100% of the parameter ('addresses' with min/max items and description). The tool description adds no new information about the parameter beyond what the schema already provides. With high schema coverage, the baseline is 3, and no additional meaning is provided, so it stays at 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Head-to-head trust comparison of 2-5 merchant addresses.' It includes a specific verb ('comparison'), resource ('merchant addresses'), and scope ('2-5'), differentiating it from siblings like check_trust (single check) and leaderboard (ranking). It also mentions the output ('winner address and a one-sentence rationale'), making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool: when you need a side-by-side trust comparison of 2-5 addresses and a winner. It does not explicitly reference alternatives or exclusions, but the '2-5' constraint and 'head-to-head' context clearly distinguish it from check_trust (single) and leaderboard (broad ranking). No misleading guidance is present.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_badge_urlAInspect
Embeddable LEGIT trust-badge SVG URL for a merchant, plus a ready-to-paste HTML snippet for the merchant's site.
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | Merchant address (Algorand / EVM / Solana) or https URL |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It states the return value (URL + snippet) but does not disclose side effects, authentication needs, or error behavior. For a getter, this is acceptable but not fully transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence that is front-loaded with the core purpose and includes essential return info. No wasted words or redundant details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with no output schema, the description adequately explains what it returns (URL + HTML snippet). However, it could mention format or error cases, but the simplicity makes it fairly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single 'address' parameter. The description adds 'merchant' context but does not meaningfully expand on the schema's already-detailed address format description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('get') and resource ('badge URL') and clearly distinguishes itself from sibling tools like check_trust and leaderboard by mentioning the embeddable SVG URL and HTML snippet.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a merchant needs a trust-badge URL but provides no explicit when-to-use or alternatives. The sibling contexts suggest different purposes, but no exclusions or guidance are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
leaderboardAInspect
Top merchants by trust score, optionally filtered to one network (e.g. base-mainnet, algorand-mainnet, solana-mainnet).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max entries to return (1-50, default 10) | |
| network | No | Optional exact-match network filter |
TDQS
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. It only states the core function and gives network examples, but does not disclose output format, default behavior, or any side effects. This is minimal for a tool that returns a list.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the key purpose and includes useful examples. Every word earns its place, with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity and the complete input schema, the description sufficiently covers the main use case. The lack of an output schema and the absence of any description of the return structure leaves a small gap, but it is not critical for this simple read tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides 100% coverage for both limit and network. The description adds value beyond the schema by giving concrete network examples (base-mainnet, algorand-mainnet, solana-mainnet), which clarifies valid values for the network parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the resource (top merchants) and metric (trust score), which distinguishes it from sibling tools like check_trust and compare_merchants. However, it lacks an explicit verb such as 'list' or 'retrieve', making it a noun phrase rather than a full action statement.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The network filter examples provide some usage context, but there is no explicit guidance on when to use this tool versus alternatives like check_trust or compare_merchants. The usage is implied rather than clearly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
4 tool updates
- First observed
check_trust - First observed
compare_merchants - First observed
get_badge_url - First observed
leaderboard
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