defi-yields-mcp
Provides a community support channel for users of the DeFi Yields MCP server, accessible via a Discord invite badge in the README.
Fetches and filters DeFi yield pool data from Ethereum blockchain, allowing analysis of APY, TVL, and yield predictions for various DeFi projects.
Retrieves yield pool data from the Solana blockchain, enabling analysis of APY metrics and yield opportunities across Solana-based DeFi projects.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@defi-yields-mcp show me the top yield pools on Ethereum by APY"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
DeFi Yields MCP
An MCP server for AI agents to explore DeFi yield opportunities, powered by DefiLlama.
Features
Data Fetching Tool: The
get_yield_poolstool retrieves DeFi yield pool data from the DefiLlama, allowing filtering by chain (e.g., Ethereum, Solana) or project (e.g., Lido, Aave).Analysis Prompt: The
analyze_yieldsprompt generates tailored instructions for AI agents to analyze yield pool data, focusing on key metrics like APY, 30-day mean APY, and predictions.Packaged for Ease: Run the server directly with
uvx defi-yields-mcp.
Related MCP server: Solana DeFi Intelligence MCP Server
Installation
To use the server with Claude Desktop, you can either install it automatically or manually configure the Claude Desktop configuration file.
Option 1: Automatic Installation
Install the server for Claude Desktop:
uvx mcp install -m defi_yields_mcp --name "DeFi Yields Server"Option 2: Manual Configuration
Locate the configuration file:
macOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonWindows:
%APPDATA%\Claude\claude_desktop_config.json
Add the server configuration:
{
"mcpServers": {
"defi-yields-mcp": {
"command": "uvx",
"args": [ "defi-yields-mcp" ]
}
}
}Restart Claude Desktop.
Examples
You can use commands like:
"Fetch yield pools for the Lido project."
"Analyze yield pools on Ethereum."
"What are the 30-day mean APYs for Solana pools?"
The get_yield_pools tool fetches and filters the data, while the analyze_yields prompt guides the LLM to provide a detailed analysis.
Example Output
Running the get_yield_pools tool with a filter for Ethereum:
[
{
"chain": "Ethereum",
"pool": "STETH",
"project": "lido",
"tvlUsd": 14804019222,
"apy": 2.722,
"apyMean30d": 3.00669,
"predictions": {
"predictedClass": "Stable/Up",
"predictedProbability": 75,
"binnedConfidence": 3
}
},
...
]License
This project is licensed under the MIT License. See the LICENSE file for details.
Available Tools
1 toolget_yield_poolsA
Fetch DeFi yield pools from the yields.llama.fi API, optionally filtering by chain or project.
Returns symbol, project, tvlUsd, apy, apyMean30d, and predictions for each pool.
Args:
chain: Optional filter for blockchain (e.g., 'Ethereum', 'Solana')
project: Optional filter for project name (e.g., 'lido', 'aave-v3')
Inputs: chain, project.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool 'get_yield_pools' has a clearly defined singular purpose of fetching DeFi yield pools with optional filters.
The single tool name 'get_yield_pools' follows a clear verb_noun pattern that would be consistent if there were more tools. There are no naming inconsistencies to evaluate in a one-tool set.
A single tool is insufficient for comprehensive DeFi yield analysis. While the tool provides basic fetching capabilities, the domain suggests needs for additional operations like historical data, comparisons, or pool-specific details that are missing.
The tool surface is severely incomplete for DeFi yield analysis. It only offers data fetching without any CRUD operations, filtering by more parameters like risk or type, or analytical tools for processing the yield data, leaving significant gaps for agent workflows.
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