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chaingpt_invoke_chat

Chat with a Web3 AI assistant to get blockchain insights, analyze crypto markets, and answer crypto-related questions using trained blockchain data and real-time information.

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: calls ChainGPT's createChatBlob API with question and chatHistory, returns the bot response in MCP format, or an error message if failed.
    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 defining the input parameters for the chaingpt_invoke_chat tool: question (required string) and chatHistory (optional string).
    export const chatSchema = {
        question: z.string().min(1, 'Question is required'),
        chatHistory: z.string(),
    }
  • Registers the 'chaingpt_invoke_chat' tool on the MCP server, providing the tool name, detailed 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,
          };
        }
      }
    );
  • Initializes the GeneralChat SDK client instance used by the handler, configured with the ChainGPT API secret key from config.
    const generalchat = new GeneralChat({
      apiKey: config.chaingpt.secretKey,
    });
  • src/tools/index.ts:4-7 (registration)
    Top-level tool registration function that invokes registerChatTools(), which in turn registers the chaingpt_invoke_chat tool.
    export const registerTools = () => {
        registerChatTools();
        registerNewsTools();
    }

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It adds a cost warning and outlines capabilities, but does not disclose response format, error handling, or performance constraints. The behavioral disclosure is partial.

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 verbose with redundant sections (e.g., capabilities list and repeated purpose statement). It could be more concise and front-loaded with essential information.

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

Completeness3/5

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

Given no annotations, no output schema, and zero schema description coverage, the description provides some context about ChainGPT's domain but misses details on response handling, error cases, and parameter usage. The contradictions reduce completeness.

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

Parameters2/5

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

The description adds context for chatHistory (default "off") but contradicts the schema, which requires it. It also introduces sdkUniqueId not present in the schema. Schema coverage is 0%, so description should compensate but instead introduces inconsistencies.

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 it invokes a chat with ChainGPT AI and gets a response based on a question, specifying it's a Web3 AI assistant. However, it does not explicitly differentiate from sibling tools chaingpt_get_ai_crypto_news and chaingpt_get_chat_history, missing an opportunity to guide selection.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes a cost warning, implying when use is appropriate, but lacks explicit guidance on when to use this tool versus its siblings. It does not state alternatives or when not to use it.

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