Monitor stablecoin peg stability in real-time across multiple blockchains with comprehensive reports and historical data
Crypto-Pegmon-MCP serves as a vital component in the Model Context Protocol (MCP) ecosystem, enabling AI applications to connect and interact with real-time stablecoin peg data. This server monitors 17 USD-pegged stablecoins across multiple blockchains, providing comprehensive reporting tools for AI agents. It helps detect depegging risks before they escalate, ensuring that AI systems can make informed decisions based on reliable financial information.
Crypto-Pegmon-MCP fetches current prices and calculates the peg deviation from $1 for USD-pegged stablecoins. This feature allows real-time monitoring of these critical tokens, ensuring that AI applications remain updated with the latest financial data.
The server generates detailed reports on stablecoin peg stability, including maximum deviation and a status classification system (Stable, Moderately Stable, Unstable). These insights are essential for AI agents to understand potential risks and take proactive measures when necessary.
Users can retrieve historical price data, up to 7 days by default, in clean Markdown table format. This feature supports detailed analysis and trend observation, providing a historical context that enhances predictive capabilities within AI systems.
Crypto-Pegmon-MCP monitors a wide range of USD-pegged stablecoins, including Tether (USDT), USDC, DAI, BUSD, TUSD, FRAX, USDD, USDS, SUSDS, EUSDE, USDY, PYUSD, GUSD, USDP, AAVE-USDC, CURVE-USD, and MIM. This broad support ensures that the server can cater to diverse financial needs.
All data is presented in a clean Markdown format, making it easy for integration into reports or dashboards. This output format simplifies the use of the server within various AI applications, ensuring seamless data consumption.
Crypto-Pegmon-MCP leverages the Model Context Protocol (MCP) to enable seamless connectivity between AI applications and financial data sources. The protocol ensures that different clients can interact with the server using a standardized interface. Here's how the architecture works:
graph TD
A[AI Application] -->|MCP Client| B[MCP Protocol]
B --> C[MCP Server]
C --> D[Data Source/Tool]
style A fill:#e1f5fe
style C fill:#f3e5f5
style D fill:#e8f5e8
MCP Client | Resources | Tools | Prompts | Status |
---|---|---|---|---|
Claude Desktop | ✅ | ✅ | ✅ | Full Support |
Continue | ✅ | ✅ | ✅ | Full Support |
Cursor | ❌ | ✅ | ❌ | Tools Only |
This compatibility matrix indicates that Crypto-Pegmon-MCP is fully integrated with Claude Desktop and Continue, while Cursor can use the tools but requires manual setup for AI prompts.
To start using Crypto-Pegmon-MCP, you need to meet certain prerequisites:
Clone the Repository:
git clone https://github.com/kukapay/crypto-pegmon-mcp.git
cd crypto-pegmon-mcp
Install Dependencies: Using uv
is recommended:
uv sync
Run the Server: Again, using uv
is recommended:
uv run main.py
Crypto-Pegmon-MCP can be used to monitor stablecoin pegs and alert AI systems to potential depegging risks. This is particularly useful for financial institutions and trading platforms that rely on accurate stablecoin values.
Technical Implementation: An AI agent can use the Analyze Peg Stability
tool to check DAI's current price and historical data every hour, triggering alerts when deviation exceeds 1%.
Developers can integrate Crypto-Pegmon-MCP into automated trading bots that monitor stablecoin pegs. These bots can buy or sell at optimal times based on the real-time peg analysis.
Technical Implementation: A bot can use the Fetch Current Price
tool to check USDC's current value and make trades accordingly, ensuring no significant deviations from $1 impact portfolio performance.
Crypto-Pegmon-MCP is compatible with the following MCP clients:
These integrations allow users to leverage Crypto-Pegmon-MCP's capabilities directly within their chosen AI application ecosystems.
Crypto-Pegmon-MCP is designed to be highly compatible with the Model Context Protocol (MCP), ensuring seamless interaction between servers and clients. Below is a detailed performance matrix:
{
"mcpServers": {
"[server-name]": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-[name]"],
"env": {
"API_KEY": "your-api-key"
}
}
}
}
A1: The server uses real-time price fetches from multiple blockchain sources to calculate peg deviations, ensuring high accuracy.
A2: While not fully supported at this time, integration is possible with custom configurations. Contact support for more details.
A3: Data updates every 5 minutes to ensure real-time monitoring.
A4: Limited customization is available through MCP protocol settings; contact the developers for advanced customization options.
A5: Yes, contributions are welcome. Visit our GitHub repository for more information on how to get involved.
Contributions and feedback from the community are vital for improving Crypto-Pegmon-MCP. If you wish to contribute or have suggestions:
For more information about the Model Context Protocol and other related resources, visit our official documentation and community forums. The MCP ecosystem offers numerous resources to help you understand and utilize the protocol effectively.
By integrating Crypto-Pegmon-MCP into AI applications, developers can enhance their systems' capabilities to handle complex financial data with ease and accuracy.
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