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CG Alpha MCP

by JCF0

elfa_trending

Read-only

Identify trending cryptocurrency tokens by analyzing market sentiment and technical indicators across specified timeframes and blockchains.

Instructions

Alias to /v2/aggregations/trending-tokens (timeframe, chain, limit, cursor).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
timeframeNo
chainNo
limitNo
cursorNo

Implementation Reference

  • Handler for the 'elfa_trending' tool (lines 185-187: alias) and the delegated 'elfa_trending_tokens' handler (189-196), which constructs query parameters and calls the generic 'elfa_query' tool to fetch from ELFA's /v2/aggregations/trending-tokens endpoint.
    "elfa_trending": async (args, meta) => {
      return toolHandlers["elfa_trending_tokens"](args, meta);
    },
    
    "elfa_trending_tokens": async (args, meta) => {
      const query = {};
      if (args && args.timeframe !== undefined) query.timeframe = args.timeframe; // "24h","7d","30d"
      if (args && args.chain     !== undefined) query.chain     = args.chain;
      if (args && args.limit     !== undefined) query.limit     = args.limit;
      if (args && args.cursor    !== undefined) query.cursor    = args.cursor;
      return toolHandlers["elfa_query"]({ path: "/v2/aggregations/trending-tokens", method: "GET", query }, meta);
    },
  • mcp-server.js:296-302 (registration)
    Registration of the 'elfa_trending' tool in the tools list, including description, input schema, and annotations.
    { name:"elfa_trending",
      description:"Alias to /v2/aggregations/trending-tokens (timeframe, chain, limit, cursor).",
      inputSchema:{ type:"object", properties:{
        timeframe:{type:"string"}, chain:{type:"string"}, limit:{type:"number"}, cursor:{type:"string"}
      }},
      annotations:{ title:"ELFA: Trending (Alias)", readOnlyHint:true, openWorldHint:true }
    },
  • Input schema definition for the 'elfa_trending' tool parameters: timeframe (string), chain (string), limit (number), cursor (string).
    inputSchema:{ type:"object", properties:{
      timeframe:{type:"string"}, chain:{type:"string"}, limit:{type:"number"}, cursor:{type:"string"}
    }},
  • Generic 'elfa_query' helper handler used by 'elfa_trending_tokens' to proxy requests to ELFA API endpoints using elfaFetch.
    "elfa_query": async (args, meta) => {
      const path = args && args.path;
      if (!path || typeof path !== "string") return { content: textContent({ error:true, message:"Missing required 'path' (string)" }), isError:true };
      const method = (args.method || "GET").toUpperCase();
      const query  = args.query || undefined;
      const body   = args.body  || undefined;
      progressNotify(meta && meta.progressToken, 1, 3, "Calling ELFA");
      const { ok, status, data } = await elfaFetch(path, { method, query, body });
      progressNotify(meta && meta.progressToken, 2, 3, "Formatting result");
      if (!ok) return { content: textContent({ error:true, status, data }), isError:true, _meta:{ status } };
      progressNotify(meta && meta.progressToken, 3, 3, "Done");
      return { content: textContent({ ok:true, status, data }) };
    },
Behavior4/5

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

Annotations indicate readOnlyHint=true and openWorldHint=true, which the description doesn't contradict. It adds value by specifying the API endpoint ('/v2/aggregations/trending-tokens'), providing context beyond annotations, though it lacks details on rate limits or response behavior. No contradiction with annotations exists.

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 a single, efficient sentence that front-loads key information (alias and endpoint). There's no wasted text, making it highly concise and well-structured for quick comprehension.

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

Completeness2/5

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

Given 4 parameters with 0% schema coverage, no output schema, and annotations only covering read/access hints, the description is incomplete. It doesn't explain what the tool returns, how parameters affect results, or differentiate it from similar tools, leaving significant gaps for agent usage.

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

Parameters2/5

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

Schema description coverage is 0%, and the description lists parameter names without explaining their meanings (e.g., what 'timeframe' or 'chain' represent). It fails to compensate for the schema's lack of descriptions, leaving parameters largely undocumented and unclear to the agent.

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

Purpose3/5

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

The description states it's an alias to a specific API endpoint with parameters listed, which gives a vague purpose. It doesn't clearly explain what the tool actually does (e.g., fetch trending tokens from ELFA) or how it differs from sibling tools like 'elfa_trending_tokens', leaving the agent to infer functionality from the endpoint name.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. The description mentions it's an alias but doesn't explain its relationship to 'elfa_trending_tokens' or other siblings, nor does it specify contexts or prerequisites for usage, offering minimal practical direction.

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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