@t2000/engine
Agent engine for conversational finance — powers the Audric consumer product.
QueryEngine orchestrates LLM conversations, financial tools, user confirmations, and MCP integrations into a single async-generator loop.
Quick Start
import { QueryEngine, AnthropicProvider, getDefaultTools } from '@t2000/engine';
import { T2000 } from '@t2000/sdk';
const agent = await T2000.create({ pin: process.env.T2000_PIN });
const engine = new QueryEngine({
provider: new AnthropicProvider({ apiKey: process.env.ANTHROPIC_API_KEY }),
agent,
tools: getDefaultTools(),
});
for await (const event of engine.submitMessage('What is my balance?')) {
switch (event.type) {
case 'text_delta':
process.stdout.write(event.text);
break;
case 'tool_start':
console.log(`\n[calling ${event.toolName}]`);
break;
case 'permission_request':
event.resolve(true);
break;
}
}
Architecture
User message
│
▼
QueryEngine.submitMessage()
│
├── LLM Provider (Anthropic Claude)
│ ├── text_delta events → streamed to client
│ └── tool_use → dispatched to tool system
│
├── Tool Orchestration (runTools)
│ ├── Read-only tools → parallel (Promise.allSettled)
│ └── Write tools → serial (TxMutex)
│
├── Permission Flow
│ └── confirm-level tools yield permission_request
│ → client resolves → tool executes or aborts
│
└── MCP Integration
├── MCP Client (McpClientManager) → consume external MCPs
└── MCP Server (buildMcpTools) → expose tools to AI clients
Modules
engine.ts | QueryEngine | Stateful conversation loop with tool dispatch |
tool.ts | buildTool | Typed tool factory with Zod validation |
orchestration.ts | runTools, TxMutex | Parallel reads, serial writes |
streaming.ts | serializeSSE, parseSSE, PermissionBridge, engineToSSE | SSE wire format + permission bridging |
session.ts | MemorySessionStore | In-memory session store with TTL |
context.ts | estimateTokens, compactMessages | Token estimation + message compaction |
cost.ts | CostTracker | Token usage + USD cost tracking with budget limits |
mcp.ts | buildMcpTools, registerEngineTools | Expose engine tools as MCP server |
mcp-client.ts | McpClientManager, McpResponseCache | Multi-server MCP client with caching |
mcp-tool-adapter.ts | adaptMcpTool, adaptAllMcpTools | Convert MCP tools into engine Tool objects |
navi-config.ts | NAVI_MCP_CONFIG, NaviTools | NAVI MCP server configuration |
navi-transforms.ts | transformRates, transformBalance, ... | Raw MCP response → engine types |
navi-reads.ts | fetchRates, fetchBalance, ... | Composite MCP read functions |
prompt.ts | DEFAULT_SYSTEM_PROMPT | Audric system prompt |
providers/anthropic.ts | AnthropicProvider | Anthropic Claude LLM provider |
Built-in Tools
Read Tools (parallel, auto-approved)
balance_check | Available, savings, debt, rewards, gas reserve |
savings_info | Positions, earnings, fund status |
health_check | Health factor with risk assessment |
rates_info | Current supply/borrow APYs |
transaction_history | Recent transaction log |
Write Tools (serial, confirmation required)
save_deposit | Deposit USDC to savings |
withdraw | Withdraw from savings |
send_transfer | Send USDC to an address |
borrow | Borrow USDC against collateral |
repay_debt | Repay outstanding debt |
claim_rewards | Claim pending yield rewards |
pay_api | Pay for an API service via MPP |
Configuration
interface EngineConfig {
provider: LLMProvider;
agent?: unknown;
mcpManager?: unknown;
walletAddress?: string;
tools?: Tool[];
systemPrompt?: string;
model?: string;
maxTurns?: number;
maxTokens?: number;
costTracker?: {
budgetLimitUsd?: number;
inputCostPerToken?: number;
outputCostPerToken?: number;
};
}
Event Types
The submitMessage() async generator yields EngineEvent:
text_delta | text | LLM streams a text chunk |
tool_start | toolName, toolUseId, input | Tool execution begins |
tool_result | toolName, toolUseId, result, isError | Tool execution completes |
permission_request | toolName, toolUseId, input, description, resolve | Write tool awaiting approval |
turn_complete | stopReason | Conversation turn finished |
usage | inputTokens, outputTokens, cacheReadTokens?, cacheWriteTokens? | Token usage report |
error | error | Unrecoverable error |
MCP Client Integration
Connect to external MCP servers (e.g., NAVI Protocol) for data:
import { McpClientManager, NAVI_MCP_CONFIG } from '@t2000/engine';
const mcpManager = new McpClientManager();
await mcpManager.connect(NAVI_MCP_CONFIG);
const engine = new QueryEngine({
provider,
agent,
mcpManager,
walletAddress: '0x...',
tools: getDefaultTools(),
});
Read tools automatically use MCP when available, falling back to the SDK.
MCP Server Adapter
Expose engine tools to Claude Desktop, Cursor, or any MCP client:
import { registerEngineTools } from '@t2000/engine';
import { McpServer } from '@modelcontextprotocol/sdk/server/mcp.js';
const server = new McpServer({ name: 'audric', version: '0.1.0' });
registerEngineTools(server, getDefaultTools());
Custom Tools
import { z } from 'zod';
import { buildTool } from '@t2000/engine';
const myTool = buildTool({
name: 'my_tool',
description: 'Does something useful',
inputSchema: z.object({ query: z.string() }),
isReadOnly: true,
permissionLevel: 'auto',
async call(input, context) {
return { data: { answer: 42 }, displayText: 'The answer is 42' };
},
});
Development
pnpm --filter @t2000/engine build
pnpm --filter @t2000/engine test
pnpm --filter @t2000/engine typecheck
pnpm --filter @t2000/engine lint
License
MIT