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AgencyOSOperationsAI AutomationAgent OrchestrationWorkflow Design
AgencyOS: Multi-Agent Automation Running 24/7
How AgencyOS deployed 15 AI agents and 30+ MCP tools to power a 10-module lead pipeline that runs around the clock.
1 min read
The Challenge
What they were facing
AgencyOS needed to scale operational output without scaling headcount. Manual workflows across research, outreach, content, and reporting were slow, inconsistent, and hard to coordinate. The team wanted a system that could run continuously, coordinate across tools, and deliver reliable output without constant supervision.
The Solution
How we helped
We built a multi-agent automation system orchestrated by a central supervisor with specialized agents assigned to critical workflows. The system is powered by the Claude Agent SDK and a Model Context Protocol (MCP) tool layer.
- 15 AI agents orchestrating core business workflows
- 30+ MCP tools connecting data, content, and execution
- 10 pipeline modules for positioning, SEO, outreach, and delivery
- Always-on runtime so the system continues working outside business hours
Key Results
15
AI Agents
Specialized roles in production
30+
MCP Tools
Connected workflow integrations
10
Pipeline Modules
Lead generation stages
24/7
Runtime
Always-on execution
The Results
What we achieved
AgencyOS now runs a durable automation layer that keeps the pipeline moving without manual bottlenecks.
Always-On Operations The agent network runs 24/7, keeping research, drafting, and follow-ups moving even while the team is offline.
Pipeline Consistency Ten dedicated modules keep the lead pipeline predictable, with each agent owning a clear slice of the workflow.
Scalable Architecture With 15 agents and 30+ tools already live, expanding coverage is a configuration change instead of a staffing problem.
Client Testimonial
The system feels like a real team: always running, always coordinated. We finally have an automation layer we can trust.
Amir Brooks
Founder at AgencyOS
Project Timeline (2-3 week delivery cycle)
Week 1: Workflow Mapping
- Identify the ten pipeline modules and owners
- Define agent roles, guardrails, and escalation paths
- Build the MCP tool inventory
Week 2: Agent Build & Orchestration
- Implement the supervisor and specialized agents
- Connect tools, data sources, and reporting
- Establish quality checks and human review loops
Week 3: Launch & Stabilize
- Deploy the system into production
- Tune prompt strategies and routing
- Establish monitoring dashboards
Tech Stack Used
- Agent Runtime: Claude Agent SDK
- Tooling Layer: Model Context Protocol (MCP)
- Dashboard: Next.js
- Hosting: Vercel
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