Covalent MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Covalent 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({
"covalent": {
"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 Covalent, 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 Covalent MCP Server
Integrate Covalent, the unified API for blockchain data, directly into your AI workflow. Access real-time and historical data across Ethereum, Polygon, Binance Smart Chain, and over 100 other supported networks using natural language.
LangChain's ecosystem of 500+ components combines seamlessly with Covalent through native MCP adapters. Connect 10 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
- Wallet Insights — Retrieve token balances, historical portfolio values, and transaction history for any wallet address.
- NFT Discovery — List NFT balances and metadata across supported chains.
- Transaction Auditing — Get full details and log events for specific transaction hashes.
- Network Monitoring — Check block details and monitor supported chain statuses.
The Covalent MCP Server exposes 10 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 Covalent to LangChain via MCP
Follow these steps to integrate the Covalent 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 10 tools from Covalent via MCP
Why Use LangChain with the Covalent MCP Server
LangChain provides unique advantages when paired with Covalent through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Covalent 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 Covalent queries for multi-turn workflows
Covalent + LangChain Use Cases
Practical scenarios where LangChain combined with the Covalent MCP Server delivers measurable value.
RAG with live data: combine Covalent tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Covalent, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Covalent tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Covalent tool call, measure latency, and optimize your agent's performance
Covalent MCP Tools for LangChain (10)
These 10 tools become available when you connect Covalent to LangChain via MCP:
get_block_details
Resolves block hashes, parent hashes, timestamps, and transaction counts for the specified chain. Get details for a specific block height
get_chains_status
Resolves block height lag, current sync status, and API availability across all supported networks. Get the current indexing status of all supported chains
get_dex_pools
Resolves liquidity pool addresses, token pairs, reserve amounts, and volume metrics for the specified DEX. List liquidity pools for a DEX on a specific chain
get_historical_portfolio
Resolves daily balances, asset valuations in USD, and historical price points for the specified wallet. Get historical daily portfolio value for a wallet address
get_nft_balances
Resolves NFT contract names, token IDs, metadata URLs, and image links across the specified blockchain network. Get NFT balances for a wallet address
get_token_balances
Resolves contract addresses, ticker symbols, token decimals, and current balances (formatted and raw) for the specified wallet and chain. Get token balances for a wallet address on a specific chain
get_token_transfers
Resolves sender/receiver addresses, transfer values, and transaction timestamps for the specified wallet. Get historical token transfers for a wallet address
get_transaction_details
Touches raw log events, decoded event parameters, and gas consumption metrics boundary. Get full details and logs for a specific transaction hash
get_transactions
Resolves transaction hashes, block heights, timestamps, and log events for the specified wallet on the given chain. Get transaction history for a wallet address
list_supported_chains
Resolves chain IDs, human-readable names, and supported features (NFTs, Dex, etc.) for each blockchain. List all blockchains supported by Covalent
Example Prompts for Covalent in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Covalent immediately.
"Show me the token balances for address '0x123...' on eth-mainnet."
"List the last 10 transactions for address '0x123...' on matic-mainnet."
"What are the NFT holdings for wallet '0x123...' on eth-mainnet?"
Troubleshooting Covalent MCP Server with LangChain
Common issues when connecting Covalent to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersCovalent + LangChain FAQ
Common questions about integrating Covalent 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 Covalent 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 Covalent to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.