Initial commit: Product OS platform

- Control Plane API with Gemini integration - Executors: Deploy, Analytics, Marketing - MCP Adapter for Continue integration - VSCode/VSCodium extension - Tool registry and run tracking - In-memory storage for local dev - Terraform infrastructure setup
2026-01-19 20:34:43 -08:00
commit b6d7148ded
58 changed files with 5365 additions and 0 deletions
--- a/platform/backend/mcp-adapter/README.md
+++ b/platform/backend/mcp-adapter/README.md
@@ -0,0 +1,103 @@
+# Product OS MCP Adapter
+
+Exposes Control Plane tools to Continue and other MCP clients.
+
+## Architecture
+
+```
+Continue (MCP client)
+        ↓
+   MCP Adapter (this server)
+        ↓
+   Control Plane API
+        ↓
+   Gemini + Executors
+```
+
+## Available Tools
+
+| Tool | Description |
+|------|-------------|
+| `deploy_service` | Deploy a Cloud Run service |
+| `get_service_status` | Check deployment health |
+| `get_funnel_analytics` | Get conversion metrics |
+| `get_top_drivers` | Understand metric drivers |
+| `generate_marketing_posts` | Create social content |
+| `chat_with_gemini` | General AI conversation |
+
+## Setup
+
+### 1. Install dependencies
+
+```bash
+cd platform/backend/mcp-adapter
+npm install
+```
+
+### 2. Make sure Control Plane is running
+
+```bash
+cd platform/backend/control-plane
+npm run dev
+```
+
+### 3. Install Continue Extension
+
+In VS Code/VSCodium:
+1. Open Extensions (Cmd+Shift+X)
+2. Search for "Continue"
+3. Install
+
+### 4. Configure Continue
+
+The configuration is already in `.continue/config.yaml`. 
+
+Or manually add to your Continue config:
+
+```yaml
+experimental:
+  modelContextProtocolServers:
+    - name: productos
+      command: npx
+      args:
+        - tsx
+        - /path/to/platform/backend/mcp-adapter/src/index.ts
+      env:
+        CONTROL_PLANE_URL: http://localhost:8080
+```
+
+### 5. Use in Continue
+
+1. Open Continue chat (Cmd+L)
+2. Enable Agent mode (click the robot icon)
+3. Ask: "Deploy my service to staging"
+
+## Environment Variables
+
+| Variable | Default | Description |
+|----------|---------|-------------|
+| `CONTROL_PLANE_URL` | `http://localhost:8080` | Control Plane API URL |
+| `TENANT_ID` | `t_mcp` | Tenant ID for tool calls |
+
+## Development
+
+```bash
+# Run directly (for testing)
+npm run dev
+
+# Build
+npm run build
+
+# Run built version
+npm start
+```
+
+## Testing
+
+```bash
+# Test tool listing
+echo '{"jsonrpc":"2.0","id":1,"method":"tools/list"}' | npm run dev
+
+# Test tool call
+echo '{"jsonrpc":"2.0","id":2,"method":"tools/call","params":{"name":"get_funnel_analytics","arguments":{}}}' | npm run dev
+```
--- a/platform/backend/mcp-adapter/package.json
+++ b/platform/backend/mcp-adapter/package.json
@@ -0,0 +1,25 @@
+{
+  "name": "@productos/mcp-adapter",
+  "version": "0.1.0",
+  "private": true,
+  "description": "MCP Adapter Server - exposes Control Plane tools to Continue and other MCP clients",
+  "type": "module",
+  "main": "dist/index.js",
+  "bin": {
+    "productos-mcp": "./dist/index.js"
+  },
+  "scripts": {
+    "dev": "tsx src/index.ts",
+    "build": "tsc -p tsconfig.json",
+    "start": "node dist/index.js"
+  },
+  "dependencies": {
+    "@modelcontextprotocol/sdk": "^1.0.0",
+    "zod": "^3.23.8"
+  },
+  "devDependencies": {
+    "@types/node": "^22.0.0",
+    "tsx": "^4.19.0",
+    "typescript": "^5.5.4"
+  }
+}
--- a/platform/backend/mcp-adapter/src/index.ts
+++ b/platform/backend/mcp-adapter/src/index.ts
@@ -0,0 +1,343 @@
+#!/usr/bin/env node
+/**
+ * Product OS MCP Adapter Server
+ * 
+ * Exposes Control Plane tools to Continue and other MCP clients.
+ * 
+ * Architecture:
+ *   Continue (MCP client) → This Adapter → Control Plane → Gemini + Executors
+ * 
+ * This keeps:
+ *   - Control Plane as the canonical API
+ *   - Auth/billing/policies centralized
+ *   - MCP as a compatibility layer
+ */
+
+import { Server } from "@modelcontextprotocol/sdk/server/index.js";
+import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
+import {
+  CallToolRequestSchema,
+  ListToolsRequestSchema,
+  ToolSchema,
+} from "@modelcontextprotocol/sdk/types.js";
+import { z } from "zod";
+
+// Control Plane URL (configurable via env)
+const CONTROL_PLANE_URL = process.env.CONTROL_PLANE_URL || "http://localhost:8080";
+const TENANT_ID = process.env.TENANT_ID || "t_mcp";
+
+// ============================================================================
+// Tool Definitions
+// ============================================================================
+
+const TOOLS: ToolSchema[] = [
+  {
+    name: "deploy_service",
+    description: "Deploy a Cloud Run service to GCP. Use when the user wants to deploy, ship, or launch code to staging or production.",
+    inputSchema: {
+      type: "object",
+      properties: {
+        service_name: {
+          type: "string",
+          description: "Name of the service to deploy"
+        },
+        repo: {
+          type: "string",
+          description: "Git repository URL (optional, defaults to current workspace)"
+        },
+        ref: {
+          type: "string",
+          description: "Git branch, tag, or commit (optional, defaults to main)"
+        },
+        env: {
+          type: "string",
+          enum: ["dev", "staging", "prod"],
+          description: "Target environment"
+        }
+      },
+      required: ["service_name"]
+    }
+  },
+  {
+    name: "get_service_status",
+    description: "Check the status of a deployed Cloud Run service. Use when the user asks about service health or deployment status.",
+    inputSchema: {
+      type: "object",
+      properties: {
+        service_name: {
+          type: "string",
+          description: "Name of the service to check"
+        },
+        region: {
+          type: "string",
+          description: "GCP region (defaults to us-central1)"
+        }
+      },
+      required: ["service_name"]
+    }
+  },
+  {
+    name: "get_funnel_analytics",
+    description: "Get funnel conversion metrics and drop-off analysis. Use when the user asks about funnels, conversions, or user journey.",
+    inputSchema: {
+      type: "object",
+      properties: {
+        funnel_name: {
+          type: "string",
+          description: "Name of the funnel to analyze (optional)"
+        },
+        range_days: {
+          type: "integer",
+          description: "Number of days to analyze (defaults to 30)"
+        }
+      }
+    }
+  },
+  {
+    name: "get_top_drivers",
+    description: "Identify top factors driving a metric. Use when the user asks why something changed or what drives conversions/retention.",
+    inputSchema: {
+      type: "object",
+      properties: {
+        metric: {
+          type: "string",
+          description: "The metric to analyze (e.g., 'conversion', 'retention', 'churn')"
+        },
+        range_days: {
+          type: "integer",
+          description: "Number of days to analyze (defaults to 30)"
+        }
+      },
+      required: ["metric"]
+    }
+  },
+  {
+    name: "generate_marketing_posts",
+    description: "Generate social media posts for a marketing campaign. Use when the user wants to create content for X, LinkedIn, etc.",
+    inputSchema: {
+      type: "object",
+      properties: {
+        goal: {
+          type: "string",
+          description: "Campaign goal (e.g., 'product launch', 'feature announcement', 'engagement')"
+        },
+        product: {
+          type: "string",
+          description: "Product or feature name"
+        },
+        channels: {
+          type: "array",
+          items: { type: "string" },
+          description: "Social channels to generate for (e.g., ['x', 'linkedin'])"
+        },
+        tone: {
+          type: "string",
+          description: "Tone of voice (e.g., 'professional', 'casual', 'excited')"
+        }
+      },
+      required: ["goal"]
+    }
+  },
+  {
+    name: "chat_with_gemini",
+    description: "Have a conversation with Gemini AI about your product, code, or anything else. Use for general questions, code explanation, or ideation.",
+    inputSchema: {
+      type: "object",
+      properties: {
+        message: {
+          type: "string",
+          description: "The message or question to send to Gemini"
+        },
+        context: {
+          type: "string",
+          description: "Additional context (e.g., code snippet, file contents)"
+        }
+      },
+      required: ["message"]
+    }
+  }
+];
+
+// ============================================================================
+// Tool Name Mapping (MCP tool name → Control Plane tool name)
+// ============================================================================
+
+const TOOL_MAPPING: Record<string, string> = {
+  "deploy_service": "cloudrun.deploy_service",
+  "get_service_status": "cloudrun.get_service_status",
+  "get_funnel_analytics": "analytics.funnel_summary",
+  "get_top_drivers": "analytics.top_drivers",
+  "generate_marketing_posts": "marketing.generate_channel_posts",
+};
+
+// ============================================================================
+// Control Plane Client
+// ============================================================================
+
+async function invokeControlPlaneTool(tool: string, input: any): Promise<any> {
+  // Step 1: Invoke the tool
+  const invokeResponse = await fetch(`${CONTROL_PLANE_URL}/tools/invoke`, {
+    method: "POST",
+    headers: { "Content-Type": "application/json" },
+    body: JSON.stringify({
+      tool,
+      tenant_id: TENANT_ID,
+      input,
+      dry_run: false
+    })
+  });
+
+  if (!invokeResponse.ok) {
+    const text = await invokeResponse.text();
+    throw new Error(`Control Plane error: ${invokeResponse.status} - ${text}`);
+  }
+
+  const invokeResult = await invokeResponse.json();
+  
+  // Step 2: Fetch the full run to get the output
+  const runResponse = await fetch(`${CONTROL_PLANE_URL}/runs/${invokeResult.run_id}`);
+  
+  if (!runResponse.ok) {
+    // Fall back to the invoke result if we can't fetch the run
+    return invokeResult;
+  }
+
+  return runResponse.json();
+}
+
+async function chatWithControlPlane(message: string, context?: string): Promise<any> {
+  const messages = [];
+  
+  if (context) {
+    messages.push({ role: "user", content: `Context:\n${context}` });
+  }
+  messages.push({ role: "user", content: message });
+
+  const response = await fetch(`${CONTROL_PLANE_URL}/chat`, {
+    method: "POST",
+    headers: { "Content-Type": "application/json" },
+    body: JSON.stringify({
+      messages,
+      autoExecuteTools: true
+    })
+  });
+
+  if (!response.ok) {
+    const text = await response.text();
+    throw new Error(`Control Plane chat error: ${response.status} - ${text}`);
+  }
+
+  return response.json();
+}
+
+// ============================================================================
+// MCP Server
+// ============================================================================
+
+const server = new Server(
+  {
+    name: "productos-mcp",
+    version: "0.1.0",
+  },
+  {
+    capabilities: {
+      tools: {},
+    },
+  }
+);
+
+// List available tools
+server.setRequestHandler(ListToolsRequestSchema, async () => {
+  return { tools: TOOLS };
+});
+
+// Handle tool calls
+server.setRequestHandler(CallToolRequestSchema, async (request) => {
+  const { name, arguments: args } = request.params;
+
+  console.error(`[MCP] Tool called: ${name}`, args);
+
+  try {
+    // Special handling for chat
+    if (name === "chat_with_gemini") {
+      const result = await chatWithControlPlane(
+        (args as any).message,
+        (args as any).context
+      );
+      
+      return {
+        content: [
+          {
+            type: "text",
+            text: result.message || JSON.stringify(result, null, 2)
+          }
+        ]
+      };
+    }
+
+    // Map MCP tool name to Control Plane tool name
+    const controlPlaneTool = TOOL_MAPPING[name];
+    if (!controlPlaneTool) {
+      throw new Error(`Unknown tool: ${name}`);
+    }
+
+    // Invoke the Control Plane
+    const run = await invokeControlPlaneTool(controlPlaneTool, args);
+
+    // Format the response
+    let responseText = "";
+    
+    if (run.status === "succeeded") {
+      responseText = `✅ **${name}** completed successfully\n\n`;
+      responseText += "**Result:**\n```json\n";
+      responseText += JSON.stringify(run.output, null, 2);
+      responseText += "\n```";
+    } else if (run.status === "failed") {
+      responseText = `❌ **${name}** failed\n\n`;
+      responseText += `**Error:** ${run.error?.message || "Unknown error"}`;
+    } else {
+      responseText = `⏳ **${name}** is ${run.status}\n\n`;
+      responseText += `**Run ID:** ${run.run_id}`;
+    }
+
+    return {
+      content: [
+        {
+          type: "text",
+          text: responseText
+        }
+      ]
+    };
+
+  } catch (error: any) {
+    console.error(`[MCP] Error:`, error);
+    return {
+      content: [
+        {
+          type: "text",
+          text: `❌ Error executing ${name}: ${error.message}`
+        }
+      ],
+      isError: true
+    };
+  }
+});
+
+// ============================================================================
+// Start Server
+// ============================================================================
+
+async function main() {
+  console.error("[MCP] Product OS MCP Adapter starting...");
+  console.error(`[MCP] Control Plane URL: ${CONTROL_PLANE_URL}`);
+  
+  const transport = new StdioServerTransport();
+  await server.connect(transport);
+  
+  console.error("[MCP] Server connected and ready");
+}
+
+main().catch((error) => {
+  console.error("[MCP] Fatal error:", error);
+  process.exit(1);
+});
--- a/platform/backend/mcp-adapter/tsconfig.json
+++ b/platform/backend/mcp-adapter/tsconfig.json
@@ -0,0 +1,14 @@
+{
+  "compilerOptions": {
+    "target": "ES2022",
+    "module": "NodeNext",
+    "moduleResolution": "NodeNext",
+    "outDir": "dist",
+    "rootDir": "src",
+    "strict": true,
+    "esModuleInterop": true,
+    "skipLibCheck": true,
+    "declaration": true
+  },
+  "include": ["src/**/*"]
+}