Verify public marketplace, retail, classified, and auction listings before an agent relies on them; return source-supported facts or explicit safe-failure states.
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Average 4.1/5 across 1 of 1 tools scored.
Only one tool exists, so there is no ambiguity. The tool's purpose is clearly distinct by default.
With a single tool, naming consistency is inherently a non-issue, but the name follows a reasonable verb_noun pattern on its own. The score is neutral as there is no pattern to evaluate across tools.
A single tool feels too thin for a server purporting to handle verification of various listing types. The tool name suggests a broad scope that would typically benefit from multiple tools for different listing categories or actions.
The server only provides a verify action. Missing are tools to search for listings, fetch historical data, or manage verification results, leading to significant gaps for agents needing comprehensive listing verification workflows.
verify_public_listingAInspectVerify a public product, marketplace, classified, auction, or other listing immediately before an agent relies on it. Return source-supported facts when retrievable and explicit removed, blocked, unreachable, unsupported, or insufficient-evidence states rather than inventing facts.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Public HTTP or HTTPS listing page URL to inspect. | |
| claim | Yes | Natural-language claim about current availability, price, and/or location. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations were provided, so the description carries the full burden. It discloses key behaviors: the tool returns 'source-supported facts when retrievable' and explicitly reports negative/uncertain states rather than hallucinating. It also clearly states it can handle multiple listing types. This provides a thorough behavioral contract for a verification tool.
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 and efficiently front-loads the purpose and usage context. Every clause serves a purpose: stating what the tool verifies, when to use it, what output to expect, and behavioral constraints. No wasted words, though a minor point is that the second sentence is somewhat long and could be slightly more structured.
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 tool has only 2 simple parameters, 100% schema coverage, no output schema, and no nested objects, the description provides sufficient context for an agent to understand the tool's purpose, usage, and output behavior. It covers the return states and the anti-hallucination guarantee. The only gap is the lack of any mention of error handling or rate limiting, but this is acceptable for a verification tool with no annotations.
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%, so the schema already documents both parameters (url and claim) with descriptions. The description reinforces that 'url' is a public listing page and 'claim' is a natural-language statement about availability/price/location. While helpful, it adds only modest value beyond the schema descriptions, earning a baseline 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 ('verify') and names concrete resource types (product, marketplace, classified, auction, listing). It clearly distinguishes the tool's role as a fact-checking step performed 'immediately before an agent relies on' a listing, which helps differentiate it from generic URL retrieval or scraping tools, even though no sibling tools are listed.
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 clearly states when to use the tool ('immediately before an agent relies on' a listing) and sets behavioral expectations for output states (explicit removed/blocked/unreachable/insufficient-evidence). It does not explicitly list alternatives or when not to use it, but the context is strong enough that an agent could infer appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$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.
Control your server's listing on Glama, including description and metadata
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For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
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