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chaingpt_invoke_chat

Ask blockchain questions to get AI-powered answers about crypto markets, smart contracts, DeFi protocols, and on-chain analytics using specialized Web3 data.

Instructions

    Invoke a chat with ChainGPT AI and get a response based on the provided question.
    Web3-native AI assistant built specifically for the crypto world. 
    It has deep blockchain expertise, enabling seamless integration of crypto-aware AI into your applications. 
    The model is trained on blockchain data (smart contracts, DeFi protocols, NFTs, DAOs) and real-time market information, 
    making it ideal for use cases like customer support, on-chain analytics, trading assistance, and community engagement

    Capabilities:
        - Aggregate any amount of web3 market statistics
        - Interact with Blockchains 
        - Live information tracking of 5,000+ cryptos.
        - AI Generated News

    ⚠️ COST WARNING: This tool makes an API call to ChainGPT which may incur costs.

    This tool allows you to interact with ChainGPT's conversational AI capabilities.

    Args:
        question (str): The question or message to send to ChainGPT.
        chatHistory (str, optional): Whether to include chat history in the request.
            Defaults to "off" if not provided. Can be set to "on" to maintain conversation context.
        sdkUniqueId (str, optional): The unique identifier for the chat.
            Defaults to a random UUID if not provided
    Returns:
        The response from ChainGPT AI to the provided question or message.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
questionYes
chatHistoryYes

Implementation Reference

  • The asynchronous handler function that executes the tool logic. It calls ChainGPT's createChatBlob API with the question and optional chatHistory, formats the response as MCP content, and handles errors by returning an error message.
    async (params) => {
      try {
        const response = await generalchat.createChatBlob({
          question: params.question,
          chatHistory: params.chatHistory,
        });
        return {
          content: [
            {
              type: "text",
              text: response.data.bot,
            },
          ],
        };
      } catch (error) {
        const errorMessage =
          error instanceof Error ? error.message : "invoke_chat_Unknown_Error";
        return {
          content: [
            {
              type: "text",
              text: errorMessage,
            },
          ],
          isError: true,
        };
      }
    }
  • The server.tool registration call that registers the 'chaingpt_invoke_chat' tool with its description, input schema, and handler function.
    server.tool(
      "chaingpt_invoke_chat",
      `
          Invoke a chat with ChainGPT AI and get a response based on the provided question.
          Web3-native AI assistant built specifically for the crypto world. 
          It has deep blockchain expertise, enabling seamless integration of crypto-aware AI into your applications. 
          The model is trained on blockchain data (smart contracts, DeFi protocols, NFTs, DAOs) and real-time market information, 
          making it ideal for use cases like customer support, on-chain analytics, trading assistance, and community engagement
    
          Capabilities:
              - Aggregate any amount of web3 market statistics
              - Interact with Blockchains 
              - Live information tracking of 5,000+ cryptos.
              - AI Generated News
    
          ⚠️ COST WARNING: This tool makes an API call to ChainGPT which may incur costs.
    
          This tool allows you to interact with ChainGPT's conversational AI capabilities.
    
          Args:
              question (str): The question or message to send to ChainGPT.
              chatHistory (str, optional): Whether to include chat history in the request.
                  Defaults to "off" if not provided. Can be set to "on" to maintain conversation context.
              sdkUniqueId (str, optional): The unique identifier for the chat.
                  Defaults to a random UUID if not provided
          Returns:
              The response from ChainGPT AI to the provided question or message.
          `,
      chatSchema,
      async (params) => {
        try {
          const response = await generalchat.createChatBlob({
            question: params.question,
            chatHistory: params.chatHistory,
          });
          return {
            content: [
              {
                type: "text",
                text: response.data.bot,
              },
            ],
          };
        } catch (error) {
          const errorMessage =
            error instanceof Error ? error.message : "invoke_chat_Unknown_Error";
          return {
            content: [
              {
                type: "text",
                text: errorMessage,
              },
            ],
            isError: true,
          };
        }
      }
    );
  • Zod schema for the tool's input parameters: 'question' (required string) and 'chatHistory' (optional string).
    export const chatSchema = {
        question: z.string().min(1, 'Question is required'),
        chatHistory: z.string(),
    }
  • Instantiation of the GeneralChat SDK client used by the handler, configured with the ChainGPT API key from config.
    const generalchat = new GeneralChat({
      apiKey: config.chaingpt.secretKey,
    });
Behavior4/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It effectively describes key traits: it's a conversational AI tool with web3 expertise, includes a cost warning for API calls, and mentions capabilities like aggregating statistics and tracking crypto information. It could improve by specifying rate limits or authentication requirements, but covers core behavioral aspects well.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately front-loaded with the core purpose, but contains some redundancy (e.g., repeating 'This tool allows you to interact...'). The capabilities list and web3 context are useful but could be more streamlined. Overall, it's informative but not maximally concise, with some sentences that could be merged or trimmed.

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 no annotations and no output schema, the description provides good contextual completeness. It covers purpose, usage context, behavioral traits (including cost warning), parameter semantics, and return value description. It lacks details on error handling or response format specifics, but is largely complete for a conversational AI tool with two parameters.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate. It provides clear semantics for both parameters: 'question' is the message to send, 'chatHistory' controls context inclusion with defaults explained. The description adds meaningful context beyond the bare schema, though it mentions an optional 'sdkUniqueId' parameter not in the schema, creating minor inconsistency.

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 tool's purpose: 'Invoke a chat with ChainGPT AI and get a response based on the provided question.' It specifies the verb ('invoke a chat'), resource ('ChainGPT AI'), and distinguishes from siblings by focusing on conversational AI rather than news retrieval or history access. The additional context about ChainGPT's web3-native capabilities further clarifies its specialized domain.

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 when to use this tool: for conversational AI interactions with ChainGPT, particularly for web3/crypto-related queries. It mentions ideal use cases like customer support, analytics, and trading assistance. However, it does not explicitly state when NOT to use it or name alternatives (e.g., when to use sibling tools like chaingpt_get_ai_crypto_news instead).

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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