VERTICAL(legal): contract risk review under LATAM law + local compliance. input=contract+country. B2B: legaltech/SMBs review LATAM contracts in seconds. [x402: 25.0 USDC on Base, pay-per-use]
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes | service input |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the behavioral disclosure burden. It discloses the task, jurisdiction, speed, target users, and the pay-per-use cost of 25.0 USDC on Base, which is useful. However, it does not explain the output format or other execution behavior, and there is no output schema to fill that 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 compact and front-loads the core purpose before supplemental pricing and target-audience details. It is information-dense without redundancy, though the market-positioning phrase adds slightly less operational value than the rest.
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 single-input tool with low complexity, the description covers the essential invocation context: what the tool does, which jurisdiction it applies to, how to compose the input, and the cost. The lack of an explicit output description is a minor gap since no output schema exists.
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 only describes the parameter as 'service input', but the description adds real meaning with 'input=contract+country'. This tells the agent what content to provide, though it leaves the exact formatting or separation of contract and country unspecified.
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 states a specific verb, resource, and scope: 'contract risk review under LATAM law + local compliance'. The LATAM qualifier clearly differentiates it from sibling tools like legal-review or general compliance tools.
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: reviewing LATAM contracts with contract and country as input, aimed at legaltech/SMBs. It does not explicitly name alternatives or provide when-not-to-use guidance, so it stops 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.
Add one secure layer between your agents and this server.
The set contains many trivially indistinct tools: ai-inference/inference, compress/comprimir, count-tokens/contar-tokens, detect-language/language-detect, and multiple overlapping OCR receipt variants. With 160 tools and pairs that differ only by language or suffix, an agent cannot reliably distinguish several capabilities.
Most names are readable lower-hyphen identifiers, but they mix action verbs, noun phrases, domain prefixes, pipeline suffixes, Spanish/English, and arbitrary demo/batch labels. There is a loose convention, but no consistent verb_noun pattern.
160 tools on one server is an extreme count and clearly unwieldy. Even as a marketplace, exposing every variant, demo, and composed bundle as a top-level MCP tool overwhelms agent selection and adds little distinct capability.
The set covers a huge range of text, image, audio, code, market, compliance, and content-workflow tasks, so many intents have some available tool. However, it is a grab-bag rather than a defined service surface, and the arbitrary demo/specialized variants make it unclear whether a needed operation truly exists or is just a duplicate.