INDUSTRY REPORT: Landscape de servidores MCP (deep, cited). input=optional scope. B2B: developers y plataformas mapean el ecosistema MCP. [x402: 75.0 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?
With no annotations, the description carries full behavioral burden. It usefully discloses the deep/cited nature of the report and the pay-per-use cost (75.0 USDC on Base), which is important operational information. However, it does not describe the return format, how the input is used beyond scoping, or any other execution behavior.
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 report type, but it reads as fragmented tags and promotional text rather than a coherent specification. Still, the pricing and scope hints are included without excessive length.
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-parameter report tool, it covers the deliverable, audience, payment, and intended scoping, which is moderately complete. But the input-required/optional contradiction and the lack of any output description leave meaningful gaps for an agent deciding whether to invoke it and how to interpret the result.
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's 100% coverage is superficial, since 'service input' explains nothing. The description adds that input is a scope, but it also says 'optional' while the schema marks it required, creating confusion. There are no examples, formats, or allowed values to help an agent construct a valid input.
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 a specific deliverable: a deep, cited industry landscape of MCP servers aimed at developers and platforms. This distinguishes it from generic report tools by naming the subject ecosystem, though the exact relationship to sibling landscape/report tools could be sharper.
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 B2B line implies an audience, but the description gives no explicit guidance on when to use this tool versus siblings like deep-research-report, market-sector-report, or x402-payments-landscape. No exclusions or alternative-selection criteria are provided.
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.