README.md•3.07 kB
Pendle Finance FastMCP Server 🚀
This repository contains a *Model Context Protocol (MCP) Server* built with *FastMCP* in Python.
It connects to *Pendle Finance* DeFi Protocol and exposes endpoints for AI agents or clients like *MCP Inspector*.
Features include:
- Fetching live yields from Pendle API
- Simulating staking and swaps
- Retrieving user DeFi portfolio
- AI-based token recommendations (simulated)
- AI future yield predictions (simulated)
âš™ Setup and Installation
1. Prerequisites
Python 3.10+ installed on your system
Node.js 16+ if you want to use MCP Inspector
2. Clone This Repo
git clone https://github.com/maneesa029/Pendle_mcp
cd Pendle_mcp
3. Create and Activate a Virtual Environment
# Create virtual environment
python -m venv venv
# Windows
.\venv\Scripts\activate
# macOS/Linux
source venv/bin/activate
4. Install Dependencies
pip install -r requirements.txt
5. Configure .env
Create a .env file in the root folder and add your configuration:
# FastAPI settings
FASTAPI_ENV=development
HOST=127.0.0.1
PORT=8000
# Pendle API (no secret key needed for public endpoints)
PENDLE_API_URL=https://api.pendle.finance/v1/yields
# Ethereum testnet (if using staking simulation or swaps)
RPC_URL=https://sepolia.infura.io/v3/YOUR_INFURA_KEY
PRIVATE_KEY=0xYOUR_TEST_PRIVATE_KEY
âš Security Warning:
Do NOT use your main wallet private key with real funds. Always use a testnet key or a small segregated account for testing.
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🔬 Running and Monitoring the Server
1. Start the Pendle MCP Server
uvicorn server:app --reload --port 8000
You should see:
INFO: Uvicorn running on http://127.0.0.1:8000
INFO: Application startup complete.
2. Open MCP Inspector (Optional)
If you want to test tools interactively:
npx @modelcontextprotocol/inspector
This will launch a local URL (e.g., http://127.0.0.1:6274)
Open the URL in your browser
In Tools tab, you’ll see all exposed Pendle MCP functions:
get_yield → fetch top yields
stake → simulate staking
swap → simulate swap
portfolio → user portfolio
predict_best_token → AI-recommended token
predict_future → future yield prediction
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✅ 3. Test via Python Client
# test_client.py
import requests
BASE = "http://127.0.0.1:8000"
print(requests.get(f"{BASE}/get_yield").json())
print(requests.post(f"{BASE}/stake", json={"user_address":"0x123","token":"PENDLE","amount":10}).json())
print(requests.get(f"{BASE}/predict_best_token").json())
---
🔹 Features
Fetch live Pendle yields from API
Simulate staking and swaps
Retrieve user DeFi portfolio
AI predicts best token to stake
AI predicts future yields for N days
Works seamlessly with MCP Inspector or any AI agent
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🔹 Optional AI Improvements
Replace random predictions with historical yield ML model (scikit-learn / Prophet)
Include portfolio optimization for multiple tokens
Connect Ethereum testnet to simulate real transactions