AI Travel Planner MCP Agent Team
A sophisticated Streamlit-based AI travel planning application that creates extremely detailed, personalized travel itineraries using multiple MCP ser…
- OpenAI
MCP Agents ·Advanced
A Streamlit app that demonstrates the multi-agent + MCP pattern: specialized AI agents that each connect to different MCP servers to handle domain-specific tasks.
ANTHROPIC_API_KEYLicense Apache-2.0 · content curated and maintained by Doutor AI.
A Streamlit app that demonstrates the multi-agent + MCP pattern: specialized AI agents that each connect to different MCP servers to handle domain-specific tasks.
Instead of one agent with all tools, The router sends your request to a specialist - a code reviewer, security auditor, researcher, or BIM engineer - each with access to only the MCP tools they need.
User Query
|
v
[Router] --> Classifies intent
|
+-- Code Review --> GitHub MCP + Filesystem MCP
+-- Security --> GitHub MCP + Fetch MCP
+-- Research --> Fetch MCP + Filesystem MCP
+-- BIM/Revit --> Custom MCP (named pipes)
git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
cd mcp_ai_agents/multi_mcp_agent_forge
pip install -r requirements.txt
streamlit run agent_forge.py
Add new agents by defining them in the AGENTS dictionary:
AGENTS["my_agent"] = Agent(
name="My Agent",
description="Handles X tasks",
system_prompt="You are an expert in X...",
mcp_servers=[{"command": "npx", "args": ["-y", "@some/mcp-server"]}]
)
Inspired by cadre-ai/Agent Forge - a production multi-agent framework for Claude Code with 17 specialized agents, persistent memory, and desktop automation.
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