AEGIS Hedging MCP Server for LangChain 4 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect AEGIS Hedging through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MultiServerMCPClient({
"aegis-hedging": {
"transport": "streamable_http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using AEGIS Hedging, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About AEGIS Hedging MCP Server
Connect your AEGIS Hedging (Revenue Intelligence) account to your AI agent to orchestrate your energy risk management and trade lifecycle. From monitoring real-time Mark-to-Market (MTM) valuations to auditing trade entries and retrieving forward market curves, your agent handles complex energy data through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with AEGIS Hedging through native MCP adapters. Connect 4 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
What you can do
- Trade Lifecycle Management — List and audit trades executed on the AEGIS Marketplace and monitor their status in your system
- Valuation & MTM — Retrieve current Mark-to-Market data and settlement estimates for your hedge positions
- Market Intelligence — Access energy forward curves, historical price data, and daily market insights
- Reporting & Compliance — Retrieve normalized data for revenue, taxes, and fees to support financial forecasting and SDR reporting
- Strategic Oversight — Quickly identify portfolio risks or hedging opportunities based on current market volatility
The AEGIS Hedging MCP Server exposes 4 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect AEGIS Hedging to LangChain via MCP
Follow these steps to integrate the AEGIS Hedging MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 4 tools from AEGIS Hedging via MCP
Why Use LangChain with the AEGIS Hedging MCP Server
LangChain provides unique advantages when paired with AEGIS Hedging through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine AEGIS Hedging MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across AEGIS Hedging queries for multi-turn workflows
AEGIS Hedging + LangChain Use Cases
Practical scenarios where LangChain combined with the AEGIS Hedging MCP Server delivers measurable value.
RAG with live data: combine AEGIS Hedging tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query AEGIS Hedging, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain AEGIS Hedging tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every AEGIS Hedging tool call, measure latency, and optimize your agent's performance
AEGIS Hedging MCP Tools for LangChain (4)
These 4 tools become available when you connect AEGIS Hedging to LangChain via MCP:
check_api_version
Check AEGIS API version
get_forward_curves
Retrieve energy forward curves
get_valuations
Get real-time MTM valuations
list_trades
List energy hedge trades
Example Prompts for AEGIS Hedging in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with AEGIS Hedging immediately.
"List all energy trades executed in the last 30 days."
"Show me the current Mark-to-Market valuation for my natural gas portfolio."
"Retrieve the energy forward curves for the next 12 months."
Troubleshooting AEGIS Hedging MCP Server with LangChain
Common issues when connecting AEGIS Hedging to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersAEGIS Hedging + LangChain FAQ
Common questions about integrating AEGIS Hedging MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
Connect AEGIS Hedging with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect AEGIS Hedging to LangChain
Get your token, paste the configuration, and start using 4 tools in under 2 minutes. No API key management needed.