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theagoralabs

Theagora MCP Server

by theagoralabs

get_market_summary

Read-only

Retrieve a global summary of Theagora exchange activity including trade volume, active functions, open orders, and top functions by volume to understand overall market conditions.

Instructions

Get a global summary of the Theagora exchange: overall trade volume, active function count, open order count, and top functions by volume. Good for understanding overall market activity before diving into specific functions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
windowNoTime window for volume data (default: 7d)

Implementation Reference

  • The MCP tool registration and handler for get_market_summary. Defines the input schema (window parameter), executes the API call via client.getMarketDataSummary(), and returns the formatted JSON result.
    // get_market_summary — Global exchange overview
    server.tool(
      'get_market_summary',
      'Get a global summary of the Theagora exchange: overall trade volume, active function count, open order count, and top functions by volume. Good for understanding overall market activity before diving into specific functions.',
      {
        window: z.enum(['24h', '7d', '30d']).optional().describe('Time window for volume data (default: 7d)'),
      },
      { readOnlyHint: true, openWorldHint: true },
      async (params) => {
        const result = await client.getMarketDataSummary({
          window: params.window,
        });
        return {
          content: [{ type: 'text' as const, text: JSON.stringify(result, null, 2) }],
        };
      }
    );
  • The AgoraApiClient method that makes the actual HTTP GET request to the /market-data/summary endpoint with optional window query parameter.
    async getMarketDataSummary(params?: { window?: string }): Promise<any> {
      return this.request('/market-data/summary', { params: params as any });
    }
  • src/index.ts:10-30 (registration)
    Main entry point that imports and calls registerMarketDataTools to register the get_market_summary tool with the MCP server.
    import { registerMarketDataTools } from './tools/market-data.js';
    import { registerAnalyticsTools } from './tools/analytics.js';
    
    export function createServer(): McpServer {
      const server = new McpServer({
        name: 'theagora',
        version: '0.1.0',
      });
    
      const client = new AgoraApiClient();
    
      // Register all tool groups
      registerDiscoveryTools(server, client);
      registerBuyingTools(server, client);
      registerSellingTools(server, client);
      registerIdentityTools(server, client);
      registerSocialTools(server, client);
      registerTrustTools(server, client);
      registerExchangeTools(server, client);
      registerMarketDataTools(server, client);
      registerAnalyticsTools(server, client);
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 does not contradict. The description adds valuable context beyond annotations by specifying the scope ('global summary') and the types of data returned (e.g., trade volume, active function count), which helps the agent understand the tool's behavior and output structure, though it could mention rate limits or data freshness.

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 front-loaded with the core purpose in the first sentence and uses a second sentence to provide usage context, with no wasted words. Every sentence adds value, making it efficient and easy to parse for an AI agent.

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

Completeness4/5

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

Given the tool's low complexity (1 optional parameter, no output schema), the description is mostly complete. It covers purpose, usage context, and data components. However, it could be slightly enhanced by mentioning the lack of output schema or potential limitations, but it adequately supports agent understanding for this simple read-only tool.

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 'window' parameter fully documented in the schema. The description does not add any parameter-specific information beyond what the schema provides, such as default behavior implications or usage tips, so it meets the baseline of 3 for high schema coverage without extra value.

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 clearly states the verb 'Get' and specifies the resource 'global summary of the Theagora exchange' with detailed components: trade volume, active function count, open order count, and top functions by volume. It distinguishes from siblings like get_market_data or get_function_analytics by emphasizing overall market activity rather than specific data points.

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?

The description provides clear context for usage: 'Good for understanding overall market activity before diving into specific functions,' which implies it should be used as an initial overview tool. However, it does not explicitly state when not to use it or name specific alternatives among siblings, such as get_market_data, which might offer more detailed market insights.

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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