Setup Guide

"Start a chat with coach_123 about leadership"
→ Executes: chat tool
→ API Call: POST /chat
→ Result: Returns thread ID and streaming expert response

// other tools are currently not exposed via MCP

{
  "mcpServers": {
    "myweave": {
      "command": "npx",
      "args": ["-y", "@mintlify/mcp-server", "https://docs.myweave.ai"]
    }
  }
}

"What APIs does myweave provide?"

"How do I authenticate with myweave?"

"Show me how to start a chat with an expert"

"Write a TypeScript function to start a chat with a myweave expert 
and handle the streaming response"

"What parameters does the myweave /chat endpoint accept?"

"Show me the response format for getting user threads"

"Start a conversation with a leadership coach about team management"
→ Uses MCP tool: chat

"Get all my conversation threads for user_123"
→ Uses MCP tool: get-user-threads

"Show me messages from my latest thread"
→ Uses MCP tool: threads (get-thread-messages has been removed, use threads endpoint instead)

Claude: "I'll help you start a conversation. To execute this, I need your myweave API key."
You: [Provide API key]
Claude: "Starting chat with leadership coach..."
Claude: [Executes POST /chat via MCP]
Claude: "Thread created! The coach says: [expert response]"

{
  "servers": {
    "myweave-docs": {
      "command": "npx",
      "args": ["-y", "@mintlify/mcp-server", "https://docs.myweave.ai"]
    }
  }
}

// Type a comment:
// TODO: integrate myweave chat API

// Cursor (using MCP):
// Queries docs.myweave.ai
// Generates complete implementation
// Includes error handling and types

"Add myweave expert chat to this React component"

"Show me how to upload files to myweave knowledge base"

npm install @modelcontextprotocol/sdk

import { MCPClient } from '@modelcontextprotocol/sdk';

// Initialize myweave MCP client
const myweaveClient = new MCPClient({
  serverUrl: 'https://docs.myweave.ai/mcp'
});

// Query documentation (no auth needed)
async function queryDocs(question: string) {
  const response = await myweaveClient.queryDocs({
    query: question,
    context: "myweave API"
  });
  
  return response;
}

// Execute API call - client handles auth prompting
async function executeAPICall(endpoint: string, params: any) {
  // MCP client will prompt for credentials when needed
  // based on OpenAPI security requirements
  const response = await myweaveClient.executeAPI({
    endpoint: endpoint,
    method: "POST",
    body: params
  });
  
  return response;
}

// Example: AI app that integrates human expertise
class HybridAIApp {
  async respond(userMessage: string) {
    // AI analyzes message
    const aiResponse = await this.llm.generate(userMessage);
    
    // Check if human expertise needed
    if (this.needsHumanExpert(userMessage)) {
      // Query myweave docs via MCP (no auth needed)
      const docs = await queryDocs("How to start expert chat?");
      
      // Execute expert consultation
      // MCP client handles auth - will prompt for JWT if needed
      const expertChat = await executeAPICall("/chat", {
        message: userMessage,
        context: { coachId: "expert_123" }
      });
      
      // Combine AI + human intelligence
      return this.synthesize(aiResponse, expertChat);
    }
    
    return aiResponse;
  }
}

// Fetch documentation index
const response = await fetch('https://docs.myweave.ai/llms.txt');
const index = await response.text();

console.log(index);
// Returns structured list of all documentation pages

// Fetch all documentation at once
const response = await fetch('https://docs.myweave.ai/llms-full.txt');
const fullDocs = await response.text();

// Use with your LLM for context
const llmResponse = await openai.chat.completions.create({
  model: "gpt-4",
  messages: [
    {
      role: "system",
      content: `You are a myweave API integration assistant. 
                Here is the complete documentation:\n\n${fullDocs}`
    },
    {
      role: "user",
      content: "How do I authenticate and start a chat?"
    }
  ]
});

Ask your AI: "What MCP tools does myweave provide?"

The myweave MCP server provides 4 tools:
1. chat - Start or continue conversations with experts
2. get-user-threads - List all conversation threads for a user
3. threads - Get full message history from a thread (replaces get-thread-messages)
4. upload-knowledge - Upload files to knowledge base

[Detailed information about each tool...]

Ask your AI: "Write a function to start a chat with myweave using the MCP chat tool"

Ask your AI: "Use the chat tool to start a conversation with coach_123 about leadership"

Claude: "To execute the chat tool, I need your myweave API key"
You: [Provide API key]
Claude: [Executes chat tool via MCP]
Claude: "Conversation started! Thread ID: 550e8400... The expert says: [response]"

Ask your AI: "What tools are available in the myweave MCP server?"