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mldsveda

PyScrappy

by mldsveda
OverviewSchemaRelated ServersScoreDiscussions
Python

get_crypto

Retrieve live cryptocurrency prices, market caps, and 24h changes for specified coins or top market-cap coins. Supports custom currencies and result limits, returning structured records for AI agents.

Instructions

Fetch live cryptocurrency market data and return a list of coin records, each with fields: id, symbol, name, current price (in vs_currency), market cap, and 24h price change (percent).

Fetches from a live crypto market data API over the network, so results reflect current prices and require internet access; no local state is read or written. When query is omitted, returns the top coins ranked by market cap. If no coins match the query, returns an empty list rather than raising.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoString of comma-separated coin ids. Example: "bitcoin, ethereum". Default None (returns top coins by market cap).
max_resultsNoInteger maximum number of coins to return. Example: 10. Default 20.
vs_currencyNoString fiat or quote currency code for prices, lowercase. Example: "usd". Allowed: any currency supported by the data source, e.g. "usd", "eur", "gbp", "jpy". Default "usd".usd

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
countNo
errorsNo
scraperNo
source_urlsNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed3 schema fields changed
    • changedInput schema / properties / max_results / description
      Previous value: -"Max coins to return (default 20)."New value: +"Integer maximum number of coins to return. Example: 10. Default 20."
    • changedInput schema / properties / query / description
      Previous value: -"Comma-separated coins (e.g. \"bitcoin, ethereum\"). Omit for top coins."New value: +"String of comma-separated coin ids. Example: \"bitcoin, ethereum\". Default None (returns top coins by market cap)."
    • changedInput schema / properties / vs_currency / description
      Previous value: -"Fiat currency for prices, e.g. \"usd\", \"eur\" (default \"usd\")."New value: +"String fiat or quote currency code for prices, lowercase. Example: \"usd\". Allowed: any currency supported by the data source, e.g. \"usd\", \"eur\", \"gbp\", \"jpy\". Default \"usd\"."
  2. Changed20 schema fields changedv1.3.3
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / max_results / description
      Added value: +"Max coins to return (default 20)."
    • removedInput schema / properties / max_results / title
      Removed value: -"Max Results"
    • addedInput schema / properties / query / description
      Added value: +"Comma-separated coins (e.g. \"bitcoin, ethereum\"). Omit for top coins."
    • removedInput schema / properties / query / title
      Removed value: -"Query"
    • addedInput schema / properties / vs_currency / description
      Added value: +"Fiat currency for prices, e.g. \"usd\", \"eur\" (default \"usd\")."
    • removedInput schema / properties / vs_currency / title
      Removed value: -"Vs Currency"
    • removedInput schema / title
      Removed value: -"get_cryptoArguments"
    • removedOutput schema / $defs
      Removed value: -{
-  "ToolError": {
-    "description": "A non-fatal problem encountered while scraping.",
-    "properties": {
-      "message": {
-        "title": "Message",
-        "type": "string"
-      },
-      "url": {
-        "title": "Url",
-        "type": "string"
-      }
-    },
-    "required": [
-      "url",
-      "message"
-    ],
-    "title": "ToolError",
-    "type": "object"
-  }
-}
    • removedOutput schema / properties / count / title
      Removed value: -"Count"
    • removedOutput schema / properties / data / title
      Removed value: -"Data"
    • removedOutput schema / properties / errors / items / $ref
      Removed value: -"#/$defs/ToolError"
    • addedOutput schema / properties / errors / items / description
      Added value: +"A non-fatal problem encountered while scraping."
    • addedOutput schema / properties / errors / items / properties
      Added value: +{
+  "message": {
+    "type": "string"
+  },
+  "url": {
+    "type": "string"
+  }
+}
    • addedOutput schema / properties / errors / items / required
      Added value: +[
+  "url",
+  "message"
+]
    • addedOutput schema / properties / errors / items / type
      Added value: +"object"
    • removedOutput schema / properties / errors / title
      Removed value: -"Errors"
    • removedOutput schema / properties / scraper / title
      Removed value: -"Scraper"
    • removedOutput schema / properties / source_urls / title
      Removed value: -"Source Urls"
    • removedOutput schema / title
      Removed value: -"ScrapeToolResult"
  3. Addedv1.2.0
  4. Removedv1.1.7
  5. Added

TDQS

A4.5/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description takes on full responsibility for behavioral disclosure. It states network dependency, confirms no local read/write, and specifies non-error behavior for empty results. These are meaningful, beyond-schema insights that help an agent anticipate side effects and edge cases.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and well-structured. The first sentence states the core purpose and return format; the second sentence adds essential behavioral and edge-case information. Every sentence earns its place, with no redundancy or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having no annotations, the combination of a complete schema, an output schema (indicated by context), and a description that covers purpose, network behavior, result format, and edge cases makes this fully adequate for an agent to select and invoke the tool correctly. No significant gaps remain.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%: all three parameters (query, max_results, vs_currency) have detailed, self-explanatory descriptions including defaults and examples. The tool description repeats some of this (e.g., query omitted returns top coins) but adds minimal new parameter-level semantics. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description begins with a specific verb and resource: 'Fetch live cryptocurrency market data' and then enumerates the exact fields returned (id, symbol, name, current price, market cap, 24h change). This clearly differentiates it from sibling tools like scrape_stock or convert_currency, which serve different financial data needs.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides clear usage context: results are live, need internet access, and no local state is affected. It also explains the behavior when query is omitted (top coins) and when no matches are found (empty list, not an error). It does not explicitly name alternatives or exclusions, but the use case is unambiguous enough for an agent to decide when to invoke it.

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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