AI Infrastructure · Systems Integration

Production-Grade AI Architecture & Systems Integration

We build, scale, and optimize enterprise AI workflows. From custom Model Context Protocol (MCP) servers to secure multi-agent systems, Myriad Daydreams turns cutting-edge LLM capabilities into reliable business automation.

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mcp-server.ts

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import { McpServer }
  from '@modelcontextprotocol/server';
import * as z from 'zod/v4';

const server = new McpServer({
  name: 'crm-bridge',
  version: '1.0.0',
});

server.registerTool(
  'lookup_account',
  {
    title: 'Look up CRM account',
    description: 'Get a CRM account by its ID',
    inputSchema: z.object({
      accountId: z.string().describe('CRM ID'),
    }),
    annotations: { readOnlyHint: true },
  },
  async ({ accountId }) => {
    const acct = await crm.get(accountId);
    const text = JSON.stringify(acct);
    return { content: [{ type: 'text', text }] };
  }
);

server ready · stdio 1 tool registered

Services

Engineering AI systems that hold up in production

From initial architecture to autonomous workflows running inside your stack.

01

AI System Architecture & Design

Prototyping multi-agent orchestrations, context window optimization, and semantic search routing.

02

Custom Enterprise Integrations

Developing custom MCP (Model Context Protocol) servers to safely bridge company data silos with Anthropic models.

03

Workflow Automation

Auditing legacy business processes and replacing friction points with autonomous agent loops and structured data extraction.

Technical Stack

Built on proven, production-ready tooling

We work across the model providers, frameworks, and cloud platforms your teams already trust.

Model Anthropic Claude API Sonnet / Opus
Protocol Model Context Protocol MCP servers & clients
Language Python Agents, pipelines, APIs
Language TypeScript MCP servers, services
Orchestration LangChain Chains & agent tooling
Retrieval LlamaIndex RAG & data indexing
Tooling Claude Code CLI Agentic dev workflows
Cloud AWS Bedrock Managed model hosting
Cloud Google Cloud Vertex AI Managed model hosting
Data Secure Vector Databases Embeddings & retrieval

Contact

Schedule a Technical Consultation

Tell us where your team is losing time, or where AI could close the gap. We'll follow up to discuss architecture, integration scope, and next steps.

1

Share your goals

Which workflows, systems, and data sources are involved.
2

Technical review

We assess your current stack, integration points, and data boundaries.
3

Architecture proposal

A scoped plan covering system design, security, and delivery phases.