Website trust checks: 0-100 safety score, verdict and community reviews (truster.info).
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Average 4/5 across 3 of 3 tools scored.
Each tool has a clearly distinct purpose: lookup retrieves domain details, search finds domains by prefix, and post_review submits a review. There is no overlap or ambiguity between them.
All tool names follow the consistent verb_noun pattern: lookup_domain, post_review, search_domains. This makes the API predictable and easy to navigate.
With exactly 3 tools, the server is well-scoped for a focused domain trust service. Each tool is necessary and covers a distinct core operation without redundancy.
The tool surface covers the essential workflows: looking up detailed trust information, searching for domains, and posting reviews. The inclusion of recent reviews in lookup_domain covers reading reviews, and the AI-agent-specific review posting avoids disrupting user ratings, making the set self-contained.
lookup_domainAInspectLook up a domain on truster.info: trust score (0-100), average rating, review count, Tranco rank and recent reviews.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | Domain name, e.g. amazon.com |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It clearly communicates a read-only lookup by listing the returned data. However, it does not disclose potential limitations like rate limits, authentication, or error behavior, so a 4 is warranted.
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, well-structured sentence: action, resource, then a colon-separated list of outputs. Every word adds value 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?
For a simple one-parameter lookup tool without an output schema, the description adequately covers the tool's purpose and return values. It is complete for the task at hand.
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 single parameter 'domain' is fully described in the schema with an example. The description does not add additional parameter-level detail, but the schema's 100% coverage establishes a baseline of 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 uses a specific verb 'Look up' and identifies the resource 'domain on truster.info' and enumerates the exact data returned (trust score, rating, review count, Tranco rank, recent reviews). This clearly distinguishes it from siblings like post_review and search_domains.
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 the tool is for retrieving reputation data for a specific domain, which is distinct from posting a review or searching domains. However, it does not explicitly state when to use it over alternatives, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
post_reviewAInspectPost a domain review on behalf of the authenticated user. Requires an OAuth access token with the "write" scope (discover via /.well-known/oauth-protected-resource). The review is labelled AI-agent-generated, shown in a separate section, and does NOT affect the human rating or trust score.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Review text (min 3 chars) | |
| domain | Yes | Domain name, e.g. amazon.com | |
| rating | Yes | Star rating 1-5 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It reveals several key behaviors: the review is labeled AI-agent-generated, shown in a separate section, and does NOT affect the human rating or trust score. This goes beyond typical descriptions. It could mention error handling or response format, but the covered behaviors are significant.
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 sentences, with the first sentence being a clear and direct statement of purpose. The second sentence is denser, packing multiple clauses but remaining within a reasonable length. Overall, it is concise and front-loaded.
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 a simple 3-parameter tool with 100% schema coverage and no output schema, the description covers the essential context: what the tool does, auth requirements, and notable side effects. It does not discuss return values or error cases, but those are not strictly necessary given the schema richness and the behavioral details already provided.
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%, and each parameter already has a meaningful description (min length, example, range). The description adds no additional parameter semantics, so the baseline of 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 action ('Post a domain review'), the resource ('domain review'), and the actor ('on behalf of the authenticated user'). It effectively distinguishes from the sibling read tools (lookup_domain, search_domains) by implying this is a write operation.
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 gives clear context for when to use the tool: to post a review for a user, and it explicitly states the OAuth token requirement with the write scope. It does not name alternatives, but the auth requirement and write nature provide sufficient usage guidance. Missing explicit when-not-to-use guidance, but the context is strong.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_domainsAInspectSearch domains on truster.info by name prefix; returns trust score and review count for matches.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Domain name or prefix |
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 input and output (trust score and review count) but does not clarify that this is a read-only operation, mention potential limitations (like result limits), or describe any error conditions or side effects. Given the absence of annotations, this is a significant gap.
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, well-structured sentence that front-loads the action ('Search domains on truster.info') and immediately specifies the input criterion and output. Every word earns its place, with no redundancy or filler.
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 covers the essential aspects: what it does, what input it accepts, and what it returns. It lacks details like result ordering, pagination, or whether authentication is required, but these are less critical for a basic search. The description is complete enough for this simplicity level.
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 already provides 100% coverage for the single parameter 'query' with 'Domain name or prefix'. The description adds the phrase 'by name prefix', which reinforces partial matching but does not add new syntax, formats, or constraints beyond what the schema already includes. 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's function with a specific verb ('Search'), a specific resource ('domains on truster.info'), and a scoping detail ('by name prefix'). It also distinguishes from sibling tools because searching by prefix (multiple matches) is different from exact lookup (lookup_domain) and from posting a review (post_review).
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 a use case (finding domains by name prefix) and notes the returned fields, but it does not explicitly state when to choose this tool over alternatives like lookup_domain, nor does it mention exclusions or prerequisites. The usage guidance is present but implicit.
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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{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
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