Skip to main content
Glama
questflowai

Aster Finance MCP Server

by questflowai

ticker_24hr

Get 24-hour rolling window price change statistics for cryptocurrency trading pairs to analyze market movements and inform trading decisions.

Instructions

24 hour rolling window price change statistics.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolNoTrading symbol

Implementation Reference

  • Handler case for the 'ticker_24hr' tool. Executes a GET request to the Aster API endpoint '/fapi/v1/ticker/24hr' using the shared makeRequest utility with the provided arguments.
    case 'ticker_24hr':
      return makeRequest('GET', '/fapi/v1/ticker/24hr', args);
  • src/index.ts:185-194 (registration)
    Registration of the 'ticker_24hr' tool in the ListTools response, including its description and input schema (optional 'symbol').
    {
      name: 'ticker_24hr',
      description: '24 hour rolling window price change statistics.',
      inputSchema: {
        type: 'object',
        properties: {
          symbol: { type: 'string', description: 'Trading symbol' },
        },
      },
    },
  • Input schema for the 'ticker_24hr' tool, defining an optional 'symbol' parameter.
    inputSchema: {
      type: 'object',
      properties: {
        symbol: { type: 'string', description: 'Trading symbol' },
      },
    },
  • Shared helper function 'makeRequest' used by all tools, including 'ticker_24hr', to perform HTTP requests to the Aster API, handling signing for authenticated endpoints and returning JSON-formatted responses.
    const makeRequest = async (method: 'GET' | 'POST' | 'DELETE', path: string, params: any, isSigned = false) => {
      try {
        let config: any = {
          method,
          url: path,
        };
    
        if (isSigned) {
          if (!API_KEY || !API_SECRET) {
            throw new McpError(ErrorCode.InvalidRequest, 'API_KEY and API_SECRET must be configured.');
          }
          params.timestamp = Date.now();
          const queryString = new URLSearchParams(params).toString();
          const signature = crypto.createHmac('sha256', API_SECRET).update(queryString).digest('hex');
          params.signature = signature;
          
          config.headers = { 'X-MBX-APIKEY': API_KEY };
        }
        
        if (method === 'GET' || method === 'DELETE') {
          config.params = params;
        } else { // POST
          config.data = new URLSearchParams(params).toString();
          config.headers = { ...config.headers, 'Content-Type': 'application/x-www-form-urlencoded' };
        }
    
        const response = await this.axiosInstance.request(config);
        return { content: [{ type: 'text', text: JSON.stringify(response.data, null, 2) }] };
      } catch (error) {
        if (axios.isAxiosError(error)) {
          throw new McpError(
            ErrorCode.InternalError,
            `Aster API error: ${error.response?.data?.msg || error.message}`
          );
        }
        throw error;
      }
    };
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'price change statistics' but fails to detail aspects like whether this is a read-only operation, potential rate limits, authentication needs, or the format of returned data. This leaves significant gaps in understanding how the tool behaves beyond its basic purpose.

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 directly states the tool's purpose without unnecessary words. It is front-loaded and appropriately sized, making it easy to understand quickly, which aligns well with best practices for conciseness.

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 the tool's complexity (providing statistics over a rolling window) and the lack of annotations and output schema, the description is incomplete. It doesn't explain what specific statistics are returned (e.g., high, low, volume), how the rolling window works, or error handling, leaving the agent with insufficient context for effective use.

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?

The input schema has 100% description coverage, with the 'symbol' parameter documented as 'Trading symbol.' The description adds no additional meaning beyond this, such as examples or constraints. Since the schema handles the parameter documentation adequately, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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

Purpose4/5

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

The description clearly states the tool's purpose as providing '24 hour rolling window price change statistics,' which is a specific verb+resource combination. However, it doesn't explicitly distinguish this from sibling tools like 'ticker_price' or 'ticker_bookTicker,' which might also provide price-related data, leaving some ambiguity about its unique role.

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?

The description offers no guidance on when to use this tool versus alternatives, such as 'ticker_price' or 'ticker_bookTicker.' It lacks context about scenarios where 24-hour statistics are preferred over other price or ticker data, providing no usage instructions or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/questflowai/aster-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server