The Graph (Web3 Indexing) MCP Server for LangChainGive LangChain instant access to 8 tools to Get Evm Historical Balances, Get Evm Holders, Get Evm Swaps, and more

Name: The Graph (Web3 Indexing)
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

LangChain is the leading Python framework for composable LLM applications. Connect The Graph (Web3 Indexing) through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

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The The Graph (Web3 Indexing) MCP Server for LangChain is a standout in the Developer Tools category — giving your AI agent 8 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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+ other MCP clients

python

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({
        "the-graph-web3-indexing": {
            "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 The Graph (Web3 Indexing), show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 The Graph (Web3 Indexing) MCP Server

Connect to The Graph to index and retrieve real-time blockchain data across multiple ecosystems. This MCP server allows your AI agent to query decentralized data from Ethereum, Polygon, Solana, and more through standardized tools and custom GraphQL subgraphs.

LangChain's ecosystem of 500+ components combines seamlessly with The Graph (Web3 Indexing) through native MCP adapters. Connect 8 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

EVM Data Access — Retrieve token transfers, top holders, and DEX swap events (Uniswap, Curve) for any EVM-compatible chain.
Solana (SVM) Integration — Fetch SPL token transfers, holders, and AMM swaps (Jupiter, Raydium) directly from the Solana network.
Historical Analysis — Access wallet balance changes in OHLCV format to track portfolio performance over time.
Custom Subgraph Queries — Execute raw GraphQL queries against any specific subgraph ID for deep, specialized data extraction.
Market Intelligence — Monitor liquidity pool activities and token distribution metrics without manual block explorer searching.

The The Graph (Web3 Indexing) MCP Server exposes 8 tools through the Vinkius. Connect it to LangChain in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 8 The Graph (Web3 Indexing) tools available for LangChain

When LangChain connects to The Graph (Web3 Indexing) through Vinkius, your AI agent gets direct access to every tool listed below — spanning web3, ethereum, solana, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

get

Get evm historical balances on The Graph (Web3 Indexing)

Get EVM historical balances

get

Get evm holders on The Graph (Web3 Indexing)

Get EVM token holders

get

Get evm swaps on The Graph (Web3 Indexing)

) for EVM chains. Get EVM DEX swaps

get

Get evm transfers on The Graph (Web3 Indexing)

Get EVM token transfers

get

Get svm holders on The Graph (Web3 Indexing)

Get SVM (Solana) token holders

get

Get svm swaps on The Graph (Web3 Indexing)

) for Solana. Get SVM (Solana) DEX swaps

get

Get svm transfers on The Graph (Web3 Indexing)

Get SVM (Solana) token transfers

query

Query subgraph on The Graph (Web3 Indexing)

Requires THE_GRAPH_API_KEY. Query a subgraph using GraphQL

Connect The Graph (Web3 Indexing) to LangChain via MCP

Follow these steps to wire The Graph (Web3 Indexing) into LangChain. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

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 8 tools from The Graph (Web3 Indexing) via MCP

Why Use LangChain with the The Graph (Web3 Indexing) MCP Server

LangChain provides unique advantages when paired with The Graph (Web3 Indexing) through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine The Graph (Web3 Indexing) 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 The Graph (Web3 Indexing) queries for multi-turn workflows

The Graph (Web3 Indexing) + LangChain Use Cases

Practical scenarios where LangChain combined with the The Graph (Web3 Indexing) MCP Server delivers measurable value.

RAG with live data: combine The Graph (Web3 Indexing) tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query The Graph (Web3 Indexing), synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain The Graph (Web3 Indexing) tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every The Graph (Web3 Indexing) tool call, measure latency, and optimize your agent's performance

Example Prompts for The Graph (Web3 Indexing) in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with The Graph (Web3 Indexing) immediately.

"Get the top 10 holders for the EVM token at 0x7fc66500c84a76ad7e9c93437bfc5ac33e2ddae9."

"Show me recent swaps for the Solana token DezXAZ8z7PnrnMcFWRSTQC8PGL9P8be3EFr9SptT5v7."

"Query the Uniswap V3 subgraph with ID 'ELUvFp... ' to get the latest pool prices."

Troubleshooting The Graph (Web3 Indexing) MCP Server with LangChain

Common issues when connecting The Graph (Web3 Indexing) to LangChain through Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

The Graph (Web3 Indexing) + LangChain FAQ

Common questions about integrating The Graph (Web3 Indexing) MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use 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?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.

Can I trace MCP tool calls in LangSmith?

Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.

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