TRADING(info): algorithmic signal (SMA/RSI/momentum) + suggested SL/TP levels for a crypto asset. INFORMATION ONLY, not financial advice. input=btc|eth|solana... [x402: 5.0 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 responsibility. It discloses two important behaviors: the output is informational only (not financial advice) and the call is pay-per-use (5.0 USDC via x402 on Base). It does not detail response format, but the core behavioral context is provided.
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 compact, front-loaded statement: the core function appears first, followed by the disclaimer and pricing. Every phrase carries informational weight, and the whole thing fits in two clauses.
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, no-output-schema tool, the description covers the essential context: expected input (crypto asset symbol), what the output contains (signal + SL/TP), the payment requirement, and the non-advice disclaimer. It falls slightly short on specifying the exact return structure, but the tool is simple enough that the gap is minor.
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 'input' description is only 'service input' — essentially no semantic value. The description compensates with concrete examples ('btc|eth|solana'), telling the agent exactly what kind of string to pass (a crypto asset symbol). This adds meaningful guidance beyond the schema.
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 function: generating algorithmic trading signals (SMA/RSI/momentum) plus stop-loss/take-profit levels for a crypto asset. It clearly separates itself from sibling tools like crypto-price (spot prices) and crypto-backtest (historical testing).
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 the tool — when an agent needs buy/sell-style signals for a crypto asset — and even clarifies that it provides information only. However, it does not explicitly name alternatives or state when not to use it, leaving the routing to the agent's inference.
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.