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Implementar a API do Jogo e o servidor MCP de Inventário

Implementaremos as seguintes APIs nesta seção:

  1. saveGame - criar ou atualizar um jogo.
  2. queryGames - retornar uma lista paginada de jogos salvos anteriormente.
  3. queryInventory - retornar uma lista paginada de itens no inventário de um jogador.
  4. queryActions - retornar o histórico de conversação para um determinado jogo.

Para definir nossas entradas e saídas da API, vamos criar nosso esquema usando Zod dentro do arquivo packages/game-api/src/schema/index.ts da seguinte forma:

import { z } from 'zod';
export const QueryInputSchema = z.object({
cursor: z.string().optional(),
limit: z.number().optional().default(100),
});
export type IQueryInput = z.TypeOf<typeof QueryInputSchema>;
export const ActionSchema = z.object({
role: z.enum(['user', 'assistant']),
content: z.string(),
messageId: z.number(),
});
export type IAction = z.TypeOf<typeof ActionSchema>;
export const GameSchema = z.object({
playerName: z.string(),
genre: z.enum(['zombie', 'superhero', 'medieval']),
lastUpdated: z.iso.datetime(),
});
export type IGame = z.TypeOf<typeof GameSchema>;
export const ItemSchema = z.object({
playerName: z.string(),
itemName: z.string(),
emoji: z.string().optional(),
lastUpdated: z.iso.datetime(),
quantity: z.number(),
});
export type IItem = z.TypeOf<typeof ItemSchema>;
export const createPaginatedQueryOutput = <ItemType extends z.ZodTypeAny>(
itemSchema: ItemType,
) => {
return z.object({
items: z.array(itemSchema),
cursor: z.string().nullable(),
});
};

Exclua o arquivo packages/game-api/src/schema/echo.ts pois não o usaremos neste projeto.

Este é o diagrama ER para nossa aplicação.

Diagram

O gerador ts#dynamodb configurou o ElectroDB, que usaremos para modelar nossos dados. Persistiremos o histórico de conversação no S3, então adicionamos uma dependência no cliente S3:

Terminal window
pnpm add @aws-sdk/client-s3@3.1116.0 --filter game-api

Substitua a entidade de exemplo gerada em packages/dungeon-db/src/entities/index.ts por nossas entidades Game e Inventory, e exclua packages/dungeon-db/src/entities/example.ts:

import { Entity } from 'electrodb';
import { getDynamoDBClient, resolveTableName } from '../client.js';
export const createGameEntity = async () =>
new Entity(
{
model: {
entity: 'Game',
version: '1',
service: 'game',
},
attributes: {
playerName: { type: 'string', required: true, readOnly: true },
genre: { type: 'string', required: true, readOnly: true },
lastUpdated: {
type: 'string',
required: true,
default: () => new Date().toISOString(),
},
},
indexes: {
primary: {
pk: { field: 'pk', composite: ['playerName'] },
sk: { field: 'sk', composite: [] },
},
},
},
{ client: getDynamoDBClient(), table: await resolveTableName() },
);
export const createInventoryEntity = async () =>
new Entity(
{
model: {
entity: 'Inventory',
version: '1',
service: 'game',
},
attributes: {
playerName: { type: 'string', required: true, readOnly: true },
lastUpdated: {
type: 'string',
required: true,
default: () => new Date().toISOString(),
},
itemName: {
type: 'string',
required: true,
},
emoji: {
type: 'string',
required: false,
},
quantity: {
type: 'number',
required: true,
},
},
indexes: {
primary: {
pk: { field: 'pk', composite: ['playerName'] },
sk: { field: 'sk', composite: ['itemName'] },
},
},
},
{ client: getDynamoDBClient(), table: await resolveTableName() },
);

O ElectroDB nos permite não apenas definir nossos tipos, mas também pode fornecer padrões para certos valores como timestamps. Além disso, o ElectroDB segue o design de tabela única que é a melhor prática ao usar DynamoDB.

Para implementar os métodos da API, faça as seguintes alterações dentro de packages/game-api/src/procedures:

import { createGameEntity } from '@dungeon-adventure/dungeon-db';
import {
GameSchema,
IGame,
QueryInputSchema,
createPaginatedQueryOutput,
} from '../schema/index.js';
import { publicProcedure } from '../init.js';
export const queryGames = publicProcedure
.input(QueryInputSchema)
.output(createPaginatedQueryOutput(GameSchema))
.query(async ({ input }) => {
const gameEntity = await createGameEntity();
const result = await gameEntity.scan.go({
cursor: input.cursor,
count: input.limit,
});
return {
items: result.data as IGame[],
cursor: result.cursor,
};
});
export const saveGame = publicProcedure
.input(GameSchema.omit({ lastUpdated: true }))
.output(GameSchema)
.mutation(async ({ input }) => {
const gameEntity = await createGameEntity();
const result = await gameEntity.put(input).go();
return result.data as IGame;
});

Exclua o arquivo echo.ts (de packages/game-api/src/procedures) pois não o usaremos neste projeto.

Depois de definirmos nossos procedimentos, para conectá-los à nossa API, atualize o seguinte arquivo:

import { t } from './init.js';
import { queryActions } from './procedures/actions.js';
import { queryGames, saveGame } from './procedures/games.js';
import { queryInventory } from './procedures/inventory.js';
export const router = t.router;
export const appRouter = router({
actions: router({
query: queryActions,
}),
games: router({
query: queryGames,
save: saveGame,
}),
inventory: router({
query: queryInventory,
}),
});
export type AppRouter = typeof appRouter;

Vamos criar um servidor MCP que permitirá ao nosso agente gerenciar itens no inventário de um jogador.

Definiremos as seguintes ferramentas para nosso agente:

  • list-inventory-items para recuperar os itens atuais do inventário do jogador
  • add-to-inventory para adicionar itens ao inventário do jogador
  • remove-from-inventory para remover itens do inventário do jogador

Para economizar tempo, definiremos todas as ferramentas inline:

import { McpServer } from '@modelcontextprotocol/sdk/server/mcp.js';
import z from 'zod';
import { createInventoryEntity } from '@dungeon-adventure/dungeon-db';
/**
* Create the MCP Server
*/
export const createServer = async () => {
const server = new McpServer({
name: 'inventory-mcp-server',
version: '1.0.0',
});
server.registerTool(
'list-inventory-items',
{
description: "List items in the player's inventory. Leave cursor blank unless you are requesting subsequent pages",
inputSchema: {
playerName: z.string(),
cursor: z.string().optional(),
},
},
async ({ playerName }) => {
const inventory = await createInventoryEntity();
const results = await inventory.query
.primary({
playerName,
})
.go();
return {
content: [{ type: 'text' as const, text: JSON.stringify(results) }],
};
},
);
server.registerTool(
'add-to-inventory',
{
description: "Add an item to the player's inventory. Quantity defaults to 1 if omitted.",
inputSchema: {
playerName: z.string(),
itemName: z.string(),
emoji: z.string(),
quantity: z.number().optional().default(1),
},
},
async ({ playerName, itemName, emoji, quantity = 1 }) => {
const inventory = await createInventoryEntity();
await inventory
.put({
playerName,
itemName,
quantity,
emoji,
})
.go();
return {
content: [
{
type: 'text' as const,
text: `Added ${itemName} (x${quantity}) to inventory`,
},
],
};
},
);
server.registerTool(
'remove-from-inventory',
{
description: "Remove an item from the player's inventory. If quantity is omitted, all items are removed.",
inputSchema: {
playerName: z.string(),
itemName: z.string(),
quantity: z.number().optional(),
},
},
async ({ playerName, itemName, quantity }) => {
const inventory = await createInventoryEntity();
// If quantity is omitted, remove the entire item
if (quantity === undefined) {
try {
await inventory.delete({ playerName, itemName }).go();
return {
content: [
{ type: 'text' as const, text: `${itemName} removed from inventory.` },
],
};
} catch {
return {
content: [
{ type: 'text' as const, text: `${itemName} not found in inventory` },
],
};
}
}
// If quantity is specified, fetch current quantity and update
const item = await inventory.get({ playerName, itemName }).go();
if (!item.data) {
return {
content: [
{ type: 'text' as const, text: `${itemName} not found in inventory` },
],
};
}
const newQuantity = item.data.quantity - quantity;
if (newQuantity <= 0) {
await inventory.delete({ playerName, itemName }).go();
return {
content: [
{ type: 'text' as const, text: `${itemName} removed from inventory.` },
],
};
}
await inventory
.put({
playerName,
itemName,
quantity: newQuantity,
emoji: item.data.emoji,
})
.go();
return {
content: [
{
type: 'text' as const,
text: `Removed ${itemName} (x${quantity}) from inventory. ${newQuantity} remaining.`,
},
],
};
},
);
return server;
};

À medida que o número de ferramentas cresce, você pode refatorá-las em arquivos separados se desejar.

Exclua os diretórios tools e resources em packages/inventory/src/mcp-server pois estes não serão usados.

O construct do Story Agent já provisiona e escreve em seu próprio bucket de sessão internamente, mas não o expõe — então nada fora do agente pode receber acesso para ler dele ainda. Como queryActions precisa ler o histórico de conversação de volta, para ilustração e simplicidade, vamos expor seu bucket de sessão interno como uma propriedade pública em common/constructs/src/app/agents/story-agent/story-agent.ts:

import { Fn, Lazy, Names, RemovalPolicy, Stack } from 'aws-cdk-lib';
import { Platform } from 'aws-cdk-lib/aws-ecr-assets';
import { Connections, IConnectable } from 'aws-cdk-lib/aws-ec2';
import {
BlockPublicAccess,
Bucket,
BucketEncryption,
IBucket,
} from 'aws-cdk-lib/aws-s3';
import { Key } from 'aws-cdk-lib/aws-kms';
import {
CfnDelivery,
CfnDeliveryDestination,
CfnDeliverySource,
LogGroup,
RetentionDays,
} from 'aws-cdk-lib/aws-logs';
import { Construct } from 'constructs';
import * as path from 'path';
import * as url from 'url';
import {
AgentRuntimeArtifact,
ProtocolType,
Runtime,
RuntimeProps,
RuntimeAuthorizerConfiguration,
} from 'aws-cdk-lib/aws-bedrockagentcore';
import {
PolicyStatement,
Effect,
ServicePrincipal,
IGrantable,
IPrincipal,
} from 'aws-cdk-lib/aws-iam';
import { IUserPool, IUserPoolClient } from 'aws-cdk-lib/aws-cognito';
import { suppressRules } from '../../../core/checkov.js';
import { RuntimeConfig } from '../../../core/runtime-config.js';
import { findWorkspaceRoot } from '../../../core/workspace.js';
export type StoryAgentProps = Omit<
RuntimeProps,
| 'runtimeName'
| 'protocolConfiguration'
| 'agentRuntimeArtifact'
| 'authorizerConfiguration'
> & {
/**
* Identity details for Cognito Authentication
*/
identity: {
userPool: IUserPool;
userPoolClient: IUserPoolClient;
};
/**
* Removal policy for the session bucket holding the agent's conversation
* history. Defaults to retaining it so a stack `destroy` doesn't silently
* delete session data — set to `RemovalPolicy.DESTROY` for sandbox/CI teardown.
*
* @default RemovalPolicy.RETAIN
*/
readonly sessionBucketRemovalPolicy?: RemovalPolicy;
};
export class StoryAgent extends Construct implements IGrantable, IConnectable {
public readonly dockerImage: AgentRuntimeArtifact;
public readonly agentCoreRuntime: Runtime;
/** The S3 bucket backing this agent's session storage — exposed so other constructs (e.g. the Game API) can be granted access to read conversation history back. */
public readonly sessionBucket: IBucket;
/** Default Gateway target name for this agent. */
public readonly agentName = 'story-agent';
/** Inbound auth — a fronting Gateway uses this to pick its outbound credential. */
public readonly auth = 'cognito';
constructor(scope: Construct, id: string, props: StoryAgentProps) {
super(scope, id);
const rc = RuntimeConfig.ensure(this);
// Resolve the bundle output directory containing the Dockerfile and built artifacts
const bundleDir = path.join(
findWorkspaceRoot(url.fileURLToPath(new URL(import.meta.url))),
'dist/packages/story/docker/story-agent',
);
this.dockerImage = AgentRuntimeArtifact.fromAsset(bundleDir, {
platform: Platform.LINUX_ARM64,
});
const {
identity,
sessionBucketRemovalPolicy = RemovalPolicy.RETAIN,
...restProps
} = props ?? {};
const sessionKey = new Key(this, 'SessionKey', {
enableKeyRotation: true,
});
// Allow CloudWatch Logs to use the session key for server access log delivery.
const stack = Stack.of(this);
sessionKey.addToResourcePolicy(
new PolicyStatement({
effect: Effect.ALLOW,
principals: [
new ServicePrincipal(`logs.${stack.region}.amazonaws.com`),
],
actions: [
'kms:Encrypt',
'kms:Decrypt',
'kms:ReEncrypt*',
'kms:GenerateDataKey*',
'kms:DescribeKey',
],
resources: ['*'],
conditions: {
ArnLike: {
'kms:EncryptionContext:aws:logs:arn': `arn:aws:logs:${stack.region}:${stack.account}:log-group:*`,
},
},
}),
);
const sessionAccessLogs = new LogGroup(this, 'SessionAccessLogs', {
retention: RetentionDays.ONE_YEAR,
encryptionKey: sessionKey,
removalPolicy: RemovalPolicy.DESTROY,
});
const sessionBucket = new Bucket(this, 'SessionBucket', {
enforceSSL: true,
removalPolicy: sessionBucketRemovalPolicy,
encryption: BucketEncryption.KMS,
encryptionKey: sessionKey,
blockPublicAccess: BlockPublicAccess.BLOCK_ALL,
});
this.sessionBucket = sessionBucket;
suppressRules(
sessionBucket,
['CKV_AWS_21'],
'Session data does not need versioning enabled',
);
suppressRules(
sessionBucket,
['CKV2_AWS_61'],
'Lifecycle configuration not required for session data',
);
suppressRules(
sessionBucket,
['CKV_AWS_144'],
'Cross-region replication not required for session data',
);
suppressRules(
sessionBucket,
['CKV2_AWS_62'],
'Event notifications not required for session data',
);
suppressRules(
sessionBucket,
['CKV_AWS_18'],
'Server access logs are delivered to CloudWatch Logs',
);
const sessionAccessLogsSource: CfnDeliverySource = new CfnDeliverySource(
this,
'SessionAccessLogsSource',
{
name: Lazy.string({
produce: () =>
Names.uniqueResourceName(sessionAccessLogsSource, {
maxLength: 60,
}),
}),
logType: 'S3_SERVER_ACCESS_LOGS',
resourceArn: sessionBucket.bucketArn,
},
);
const sessionBucketPolicy = sessionBucket.policy;
if (sessionBucketPolicy) {
sessionAccessLogsSource.node.addDependency(sessionBucketPolicy);
}
const sessionAccessLogsDestination: CfnDeliveryDestination =
new CfnDeliveryDestination(this, 'SessionAccessLogsDestination', {
name: Lazy.string({
produce: () =>
Names.uniqueResourceName(sessionAccessLogsDestination, {
maxLength: 60,
}),
}),
destinationResourceArn: sessionAccessLogs.logGroupArn,
});
const sessionAccessLogsDelivery = new CfnDelivery(
this,
'SessionAccessLogsDelivery',
{
deliverySourceName: sessionAccessLogsSource.name,
deliveryDestinationArn: sessionAccessLogsDestination.attrArn,
},
);
sessionAccessLogsDelivery.addDependency(sessionAccessLogsSource);
this.agentCoreRuntime = new Runtime(this, 'StoryAgent', {
runtimeName: Lazy.string({
produce: () =>
Names.uniqueResourceName(this.agentCoreRuntime, { maxLength: 40 }),
}),
protocolConfiguration: ProtocolType.HTTP,
agentRuntimeArtifact: this.dockerImage,
authorizerConfiguration: RuntimeAuthorizerConfiguration.usingCognito(
identity.userPool,
[identity.userPoolClient],
),
// Receive the caller's Authorization header (validated by the authorizer).
requestHeaderConfiguration: {
allowlistedHeaders: ['Authorization'],
},
...restProps,
environmentVariables: {
RUNTIME_CONFIG_APP_ID: rc.appConfigApplicationId,
...restProps?.environmentVariables,
},
});
// Grant access for the agent to invoke bedrock models
this.agentCoreRuntime.addToRolePolicy(
new PolicyStatement({
actions: [
'bedrock:InvokeModel',
'bedrock:InvokeModelWithResponseStream',
],
resources: [
'arn:aws:bedrock:*:*:foundation-model/*',
'arn:aws:bedrock:*:*:inference-profile/*',
],
}),
);
sessionBucket.grantReadWrite(this.agentCoreRuntime);
rc.grantReadAppConfig(this.agentCoreRuntime);
rc.set('agentcore', 'agentRuntimes', {
...rc.get('agentcore').agentRuntimes,
StoryAgent: {
arn: this.agentCoreRuntime.agentRuntimeArn,
session: {
bucketName: sessionBucket.bucketName,
},
},
});
rc.set('connection', 'agentRuntimes', {
...rc.get('connection').agentRuntimes,
StoryAgent: this.agentCoreRuntime.agentRuntimeArn,
});
}
/**
* The principal to grant permissions to.
*/
public get grantPrincipal(): IPrincipal {
return this.agentCoreRuntime.grantPrincipal;
}
/**
* Network connections for this agent runtime.
*/
public get connections(): Connections {
return this.agentCoreRuntime.connections;
}
/**
* The HTTPS invocation URL of the runtime.
*/
public get invocationUrl(): string {
// The URL must URL-encode the runtime ARN (':' -> '%3A', '/' -> '%2F').
// The ARN is a CDK token, so encode at deploy time via Fn.join/Fn.split.
const encodedArn = Fn.join(
'%2F',
Fn.split(
'/',
Fn.join('%3A', Fn.split(':', this.agentCoreRuntime.agentRuntimeArn)),
),
);
return `https://bedrock-agentcore.${Stack.of(this).region}.amazonaws.com/runtimes/${encodedArn}/invocations?qualifier=DEFAULT`;
}
}

O construct DungeonDb gerado por ts#dynamodb já provisiona nossa tabela, então só precisamos instanciá-lo em nossa stack e conceder à API do Jogo e ao servidor MCP de Inventário as permissões que eles precisam. Atualize packages/infra/src/stacks/application-stack.ts da seguinte forma:

import {
DungeonDb,
GameApi,
GameUI,
InventoryMcpServer,
StoryAgent,
UserIdentity,
suppressRules,
} from '@dungeon-adventure/common-constructs';
import { Stack, StackProps, CfnOutput, RemovalPolicy } from 'aws-cdk-lib';
import { TableEncryption } from 'aws-cdk-lib/aws-dynamodb';
import { Construct } from 'constructs';
export class ApplicationStack extends Stack {
constructor(scope: Construct, id: string, props?: StackProps) {
super(scope, id, props);
const userIdentity = new UserIdentity(this, 'UserIdentity');
// Sandbox-friendly: allow the table to be deleted with the stack.
const dungeonDb = new DungeonDb(this, 'DungeonDb', {
deletionProtection: false,
removalPolicy: RemovalPolicy.DESTROY,
encryption: TableEncryption.DEFAULT,
});
suppressRules(
dungeonDb.table,
['CKV_AWS_119'],
'Sandbox stack uses the AWS owned key so it can be torn down and recreated freely',
);
const gameApi = new GameApi(this, 'GameApi', {
integrations: GameApi.defaultIntegrations(this).build(),
});
dungeonDb.grantReadData(gameApi.integrations['games.query'].handler);
dungeonDb.grantReadData(gameApi.integrations['inventory.query'].handler);
dungeonDb.grantReadWriteData(gameApi.integrations['games.save'].handler);
const mcpServer = new InventoryMcpServer(this, 'InventoryMcpServer');
dungeonDb.grantReadWriteData(mcpServer.agentCoreRuntime);
// Use Cognito for user authentication with the agent
const storyAgent = new StoryAgent(this, 'StoryAgent', {
identity: userIdentity,
});
// The agent's own session bucket already persists conversation history via
// S3SessionManager; grant the Game API read access so it can replay it.
storyAgent.sessionBucket.grantRead(
gameApi.integrations['actions.query'].handler,
);
new CfnOutput(this, 'StoryAgentArn', {
value: storyAgent.agentCoreRuntime.agentRuntimeArn,
});
new CfnOutput(this, 'InventoryMcpArn', {
value: mcpServer.agentCoreRuntime.agentRuntimeArn,
});
// Grant the agent permissions to invoke our mcp server
mcpServer.grantInvokeAccess(storyAgent);
// Grant the authenticated role access to invoke the api
gameApi.grantInvokeAccess(userIdentity.identityPool.authenticatedRole);
new GameUI(this, 'GameUI');
}
}

Não há necessidade de implantar na AWS para experimentar nossa API — o target dev executa a API do Jogo contra o DynamoDB Local. Como conectamos a API do Jogo ao projeto DungeonDb no Módulo 1, este target também inicia o DynamoDB Local automaticamente.

Primeiro, corrija quaisquer problemas de lint:

Terminal window
pnpm lint

Em seguida, construa a base de código:

Terminal window
pnpm build

Inicie a API do Jogo localmente com o target dev, que também inicializa o DynamoDB Local:

Terminal window
pnpm nx dev game-api

Uma vez que seu servidor esteja funcionando, consulte a lista (vazia) de jogos:

Terminal window
curl -X GET 'http://localhost:2022/games.query?input=%7B%7D'

Você verá uma lista vazia:

{"result":{"data":{"items":[],"cursor":null}}}

Agora salve um jogo:

Terminal window
curl -X POST 'http://localhost:2022/games.save' \
-H 'Content-Type: application/json' \
-d '{"playerName":"Alice","genre":"zombie"}'

O salvamento retorna o jogo persistido (com o timestamp lastUpdated que a entidade define para você):

{"result":{"data":{"playerName":"Alice","genre":"zombie","lastUpdated":"..."}}}

Consulte novamente para confirmar que está persistido no DynamoDB Local:

Terminal window
curl -X GET 'http://localhost:2022/games.query?input=%7B%7D'

Esta resposta agora inclui o jogo salvo:

{"result":{"data":{"items":[{"playerName":"Alice","genre":"zombie","lastUpdated":"..."}],"cursor":null}}}

Você pode parar o servidor local (Ctrl+C) quando terminar.

Tarefa 5: Testar o servidor MCP de Inventário localmente

Seção intitulada “Tarefa 5: Testar o servidor MCP de Inventário localmente”

Podemos experimentar as ferramentas do servidor MCP com o MCP Inspector usando o target mcp-server-inspect gerado:

Terminal window
pnpm nx mcp-server-inspect inventory

Isso serve o servidor MCP localmente (inicializando o DynamoDB Local também) e lança o MCP Inspector em http://localhost:6274 pré-configurado para se conectar a ele. Clique em Connect, mude para a aba Tools, clique em List Tools, e experimente add-to-inventory (por exemplo, playerName: Alice, itemName: Rusty Sword, emoji: ⚔️) seguido de list-inventory-items para vê-lo persistido no DynamoDB Local. Pare o servidor (Ctrl+C) quando terminar.

Parabéns, você construiu e testou sua primeira API tRPC e servidor MCP contra uma tabela DynamoDB local! 🎉🎉🎉