DeepCore MCP Store

Industry Milestone: The Birth of Crypto's First MCP Store on DeepCore

DeepCore's MCP Store is the web3 first service and data trading platform dedicated to the Model Context Protocol (MCP), enabling the publishing of Web3 data and AI Agents as services. Just as Apple's App Store revolutionized mobile ecosystems, MCP Store signifies a paradigm shift in how AI capabilities and on-chain data are created, shared, and commercialized.

DeepCore MCP Store serves as a pioneering platform that enables seamless integration of AI agents with diverse Web3 resources.

This groundbreaking platform allows users to:

• Publish mainstream Web3 market data as MCP services

• Deploy successful AI Agents from DeepCore as monetizable MCP services

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I. Core Innovations

1. Pioneering MCP Services

   • Web3 Data as MCP Services: Seamlessly publish and trade mainstream Web3 data streams as standardized MCP modules

   • AI Agent Monetization: Deploy successful DeepCore AI Agents as MCP services, enabling developers to earn global royalties

2. Largest MCP Network

   • Discover MCP Servers & Clients: Access the largest MCP repository, ultimately covering 1,000+ MCP data providers

3. Token-Driven Economy (Planned)

   • $DPCORE Integration:

     • Publish & Earn.

     • Governance & Growth.

   • Liquidity Mining.

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II. DeepCore MCP Store: Curated MCP Plugins

The DeepCore MCP Store comes pre-loaded with multiple curated MCP plugins that can be added to your Agent with one-click during creation.

MCP Publishing

Developers can publish their Agents to MCP Store (using SSE mode), enabling AI assistants like Claude to make real-time calls to DeepCore Agents.

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III. MCP Protocol: STDIO vs SSE

The MCP protocol supports two distinct communication modes between MCP Servers and Clients:

STDIO (Standard Input/Output)

• "Face-to-face conversation" model

• Client and server communicate directly through local process stdin/stdout

• Example: During local development, your script launches via command line and exchanges data directly with MCP server without network

• Configuration example (local MongoDB integration):

json复制下载

{
  "mcpServers": {
    "mongodb": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-filesystem",
        "~/Downloads"
      ]
    }
  }
}

SSE (Server-Sent Events)

• "Hotline call" model

• Client connects to remote server via HTTP, enabling server push

• Example: AI assistant calling weather API with continuous updates

• Configuration example:

{
  "mcpServers": {
    "browser-use-mcp-server": {
      "url": "http://localhost:8000/sse"
    }
  }
}

Key Difference: STDIO requires downloading MCP Server locally, while SSE calls remote-hosted servers via HTTP. STDIO provides standardized I/O for seamless program interoperability.

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MCP Use Cases

MCP has been adopted in multiple real-world scenarios:

Case	Implementation	Benefit
OpenAI	Agent SDK supports MCP for external tool integration	Simplifies multi-step task execution
Cursor	Enhances software development via API/codebase automation	Streamlines dev workflows
Cloudflare	Shifts from local to cloud-hosted MCP servers	Reduces config complexity and improves multi-tenant security

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Python Code Example (SSE Client)

import asyncio
from mcp.client.sse import sse_client
from mcp import ClientSession

async def main():
    async with sse_client("https://deepcore.top/mcp/assistant/0bb0d57e-492e-4461cbb40da?api-key=tk_e5d65e604b9a6") as streams:
        async with ClientSession(*streams) as session:
            await session.initialize()
            
            # List available tools
            print(await session.list_tools())
            
            # Call specific tool
            response = await session.call_tool('Dexranking', {'message': 'hello world'})
            print(response)

if __name__ == '__main__':
    asyncio.run(main())

IV. Why MCP Store is Revolutionary?

• First-Mover Advantage: The only platform transforming Web3 data and AI Agents into tradable, composable assets

• Data Superiority: Building the most comprehensive MCP marketplace covering Web3 data services (including valuable Web2 data)

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The "App Store" for Web3 AI Just as App Store propelled mobile apps into a trillion-dollar economy, MCP Store aims to become the liquidity hub for Web3 AI's future:

• For Data Providers: Rapidly deploy and monetize AI models as MCP services

• For Developers: Integrate battle-tested MCP services into workflows

Feature	Description
WEB3 Data Publishing	Enables publishing mainstream WEB3 market data as MCP services, providing real-time cryptocurrency insights.
AI Agent Deployment	Allows deployment of successful AI Agents from DeepCore as monetizable MCP services.
Token Economics	Integrated with $DPCORE token economics, featuring governance and reward mechanisms to incentivize participation.
Server/Client Network	The largest collection of crypto MCP servers for developers to discover and utilize.
User-Friendly Interface	App Store-like intuitive interface for service management and deployment.