import { createMcpClient } from "@fluxy-chat/sdk";

const mcp = createMcpClient({
  transport: "http",
  url: "https://mcp.example.com/sse",
  // or stdio: { command: "npx", args: ["-y", "@modelcontextprotocol/server-git"] }
});

// List available tools
const tools = await mcp.listTools();
// [{ name: "git_status", description: "...", inputSchema: {...} }, ...]

// List resources
const resources = await mcp.listResources();

import { convertMcpTools } from "@fluxy-chat/sdk";

const mcpTools = await mcp.listTools();
const fluxyTools = convertMcpTools(mcpTools);
// Each MCP tool becomes a FluxyChat tool with execute(), description, inputSchema

// Use with agent
const agent = createAgent({
  model: "gpt-4o",
  tools: [...fluxyTools, ...builtInTools],
});

const resources = await mcp.listResources();

// Resources can be:
// - File contents (e.g., "file:///repo/README.md")
// - Database queries (e.g., "postgres://.../query/users")
// - API responses (e.g., "https://api.github.com/repos/...")

for (const resource of resources) {
  const content = await mcp.readResource(resource.uri);
  // Inject as context in the agent's system prompt
}

# Register an MCP server
curl -X POST "$WORKER_URL/admin/mcp-servers" \
  -H "Authorization: Bearer $ADMIN_JWT" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "github",
    "transport": "http",
    "url": "https://mcp.github.com/sse",
    "toolFilter": ["git_status", "git_diff", "create_issue"]
  }'