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ChainFETCH MCP Server

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by chainfetch

get_block_summary

Generate AI-powered summaries for specific Ethereum blocks to understand blockchain activity and data insights.

Instructions

Get AI-generated summary for a specific block

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
block_numberYesThe block number to get summary for

Implementation Reference

  • Handler case for the get_block_summary tool. Executes by calling makeRequest to the ChainFETCH blocks summary API endpoint with the provided arguments.
    case 'get_block_summary':
      return await this.makeRequest('/api/v1/ethereum/blocks/summary', 'GET', args, null, token);
  • Schema definition for the get_block_summary tool, including name, description, and input schema requiring a block_number string.
    {
      name: 'get_block_summary',
      description: 'Get AI-generated summary for a specific block',
      inputSchema: {
        type: 'object',
        properties: {
          block_number: {
            type: 'string',
            description: 'The block number to get summary for',
          },
        },
        required: ['block_number'],
      },
    },
  • Supporting utility method makeRequest that handles all API calls to ChainFETCH, including authentication with API token, query parameter building, and error handling. This is the core implementation behind the tool's API proxy logic.
    async makeRequest(endpoint, method = 'GET', params = {}, body = null, token = null) {
      const chainfetchToken = token || process.env.CHAINFETCH_API_TOKEN;
      
      if (!chainfetchToken) {
        throw new McpError(
          ErrorCode.InvalidRequest,
          'CHAINFETCH_API_TOKEN is required'
        );
      }
    
      const url = new URL(`${API_BASE_URL}${endpoint}`);
      
      // Add query parameters for GET requests
      if (method === 'GET' && Object.keys(params).length > 0) {
        Object.entries(params).forEach(([key, value]) => {
          if (value !== undefined && value !== null) {
            if (Array.isArray(value)) {
              value.forEach(v => url.searchParams.append(`${key}[]`, v));
            } else {
              url.searchParams.append(key, value.toString());
            }
          }
        });
      }
    
      const fetchOptions = {
        method,
        headers: {
          'Authorization': `Bearer ${chainfetchToken}`,
          'Content-Type': 'application/json',
        },
      };
    
      if (body && method !== 'GET') {
        fetchOptions.body = JSON.stringify(body);
      }
    
      const response = await fetch(url.toString(), fetchOptions);
      
      if (!response.ok) {
        const errorText = await response.text();
        throw new McpError(
          ErrorCode.InternalError,
          `API request failed: ${response.status} ${response.statusText} - ${errorText}`
        );
      }
    
      return await response.json();
    }
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'AI-generated summary' but doesn't explain what that entails (e.g., format, length, potential inaccuracies, rate limits, or authentication needs). This leaves significant gaps in understanding how the tool behaves beyond basic functionality.

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's appropriately sized and front-loaded, making it easy to parse quickly.

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 complexity of AI-generated content and lack of annotations or output schema, the description is incomplete. It doesn't address key aspects like output format, potential errors, or how it differs from other block tools, leaving the agent with insufficient context for reliable 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?

Schema description coverage is 100%, with the single parameter 'block_number' well-documented in the schema. The description doesn't add any meaning beyond this (e.g., format examples like hex or decimal, valid ranges), so it meets the baseline for adequate but not enhanced parameter semantics.

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 verb ('Get') and resource ('AI-generated summary for a specific block'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_block_info' or 'search_blocks_llm', which might also provide block-related information but with different outputs or methods.

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 provides no guidance on when to use this tool versus alternatives. With many sibling tools available (e.g., 'get_block_info', 'search_blocks_llm'), there's no indication of when this AI-generated summary is preferred over other block-related queries, leaving usage context unclear.

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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