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ChainFETCH MCP Server

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by chainfetch

get_transaction_summary

Generate AI-powered summaries for Ethereum transactions using transaction hashes to simplify blockchain analysis.

Instructions

Get AI-generated summary for a specific transaction

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
transaction_hashYesThe transaction hash to get summary for

Implementation Reference

  • index.js:240-253 (registration)
    Registration of the 'get_transaction_summary' tool in the ListToolsRequestSchema handler, including its description and input schema definition.
    {
      name: 'get_transaction_summary',
      description: 'Get AI-generated summary for a specific transaction',
      inputSchema: {
        type: 'object',
        properties: {
          transaction_hash: {
            type: 'string',
            description: 'The transaction hash to get summary for',
          },
        },
        required: ['transaction_hash'],
      },
    },
  • Handler implementation for the get_transaction_summary tool within the handleToolCall switch statement. It forwards the request to the ChainFETCH API endpoint for transaction summaries.
    case 'get_transaction_summary':
      return await this.makeRequest('/api/v1/ethereum/transactions/summary', 'GET', args, null, token);
  • Helper method 'makeRequest' used by the tool handler to make authenticated HTTP requests to the ChainFETCH API base URL.
    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. It states the tool 'Get[s] AI-generated summary', implying a read-only operation that might involve AI processing, but doesn't disclose behavioral traits such as rate limits, authentication needs, response format, or potential errors. This leaves significant gaps for an AI agent to understand how to invoke it effectively.

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 any wasted words. It is front-loaded and appropriately sized for a simple tool, making it easy for an AI agent 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 a tool that generates AI summaries (implying potential processing nuances) and the lack of annotations and output schema, the description is incomplete. It doesn't explain what the summary contains, how it's formatted, or any behavioral aspects like latency or errors, leaving the AI 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?

The input schema has 100% description coverage, with the single parameter 'transaction_hash' clearly documented. The description adds no additional meaning beyond what the schema provides, such as format examples or constraints. With high schema coverage, 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 verb 'Get' and the resource 'AI-generated summary for a specific transaction', which is specific and actionable. However, it doesn't distinguish itself from sibling tools like 'get_transaction_info' or 'search_transactions_*', leaving some ambiguity about when to use this versus those alternatives.

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 like 'get_transaction_info' or the various search tools. It mentions 'specific transaction' but doesn't clarify if this is for summarized vs. detailed views or how it differs from other transaction-related tools in the sibling list.

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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