Showcase: ApeRAG - Production GraphRAG Platform Built with mcp-agent

Hi mcp-agent team!

We built ApeRAG using mcp-agent as our core agent framework.

Live demo: https://rag.apecloud.com/

About ApeRAG

Production-ready RAG platform with Graph RAG, vector search, and intelligent AI agents.

How We Use mcp-agent

Agent Sessions:

from mcp_agent.agents.agent import Agent
from mcp_agent.workflows.llm.augmented_llm_openai import OpenAIAugmentedLLM

# Per-chat agent sessions with memory
self.agent = Agent(name="aperag_agent", server_names=["aperag"])
self.llm = await self.agent.attach_llm(OpenAIAugmentedLLM)

MCP App Factory:

from mcp_agent.app import MCPApp
from mcp_agent.config import Settings, MCPSettings

mcp_app = MCPApp(name="aperag_agent", settings=Settings(
    mcp=MCPSettings(servers={"aperag": MCPServerSettings(...)})
))

Event Processing:

from mcp_agent.logging.listeners import EventListener

class AgentEventListener(EventListener):
    async def handle_event(self, event: Event):
        # Route tool results to chat sessions by trace_id

Production Features

• Multi-tenant sessions with isolated memory
• Custom MCP server for knowledge base operations
• Real-time tool processing with event routing
• Internationalization (English/Chinese)
• Enterprise error handling and retry logic

Scale

Currently serving thousands of users in production with mcp-agent powering our intelligent chat system.

Would love to be featured as an example! The project is open source (Apache 2.0).

Thanks for the amazing framework!