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AI Agency Ops

Independent Project

Multi-Agent Orchestration

30+
Agents
Specialized roles
6
Providers
Multi-LLM routing
MCP
Protocol
Cross-agent tools
Vector
Memory
Persistent context

The Challenge

Managing 30+ specialized AI agents across different LLM providers, communication channels, and tool integrations requires a unified orchestration layer with cross-agent coordination.

The Solution

Built a unified multi-agent platform managing 30+ specialized agents — from code automation and content generation to IoT control and knowledge management — with Model Context Protocol integration and real-time event coordination.

What It Does

AI Agency Ops is a production-grade platform that orchestrates 30+ specialized AI agents. It provides unified context management, real-time event streaming via Redis, and Model Context Protocol (MCP) for seamless tool sharing across agent boundaries.

How It Works

Built on LangGraph state machines with vector memory persistence. Agents communicate via Redis Streams event bus. MCP enables tools to be shared as capabilities rather than possessions. Multi-LLM routing intelligently selects providers based on query type.

Process Flow

1Intent Recognition (NLP)
2Agent Selection (Matching)
3Context Retrieval (Vector)
4Tool Execution (MCP)
5Cross-Agent Coordination

Key Innovations

Model Context Protocols for cross-agent tool sharing
LangGraph state machines for complex workflows
Vector memory for context persistence
Real-time event bus with Redis Streams
Multi-LLM routing across 6 providers
30+ specialized agent templates

Technologies Used

ClaudeGeminiGPT-4KimiOllamaQwenPythonFastAPILangGraphRedisMCPTelegram APIWhatsApp APIGitHub API

Performance Metrics

34agents
Active Agents
Production agents across 3 clusters
+4
47tools
Shared Tools
MCP-enabled cross-agent capabilities
+12
34%
Cost Savings
Multi-LLM routing optimization
+8%
350ms
Response Time
Average end-to-end latency
-120ms

Interested in working together?

Let's discuss how AI enablement can transform your operations.

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