How to Use the Nearblocks (Near Blockchain Explorer API) MCP in LangChain

Q: How do I start using the Nearblocks (Near Blockchain Explorer API) tools with my LangChain agent?

First, install the langchain-mcp-adapters package. Then, instantiate the MultiServerMCPClient with your Vinkius endpoint. Calling client.gettools() returns a list of functions you can pass directly to your agent's constructor.

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Connect Nearblocks (Near Blockchain Explorer API) MCP to LangChain

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Setup Nearblocks (Near Blockchain Explorer API) with LangChain

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Build On-Chain Workflows

This isn't just about fetching data. It's about creating sequences that react to on-chain events. Your LangChain agent can use `get_account_transactions` to find a specific deposit, extract the transaction hash, and then feed it directly into `get_transaction_details` to check the gas fees. Each tool is a building block for a larger, automated task. You can design agents that monitor specific accounts. For instance, an agent could periodically call `get_account_tokens`, and if a new token appears, it could then use `get_token_details` to find the contract's origin. This lets you build custom alerting and reporting systems for any Near account without writing a full-blown indexer.

Reason Across Live Blockchain Data

Give your agents the ability to make decisions based on live network conditions. A trading agent might start by calling `get_network_stats` to check current gas prices before deciding whether to execute a series of actions. This is how you build logic that's aware of its environment. Combine tools for more complex analysis. For example, pull a list of recent blocks with `get_latest_blocks`, then have your agent iterate through them, calling `get_block_details` for each one to find specific producer information. This MCP Server gives your agents the raw material they need to reason about the state of the Near protocol.

Connect Near Data to Anything

The real point of using this with LangChain is connecting blockchain data to other systems. You can create a chain that takes output from `get_account_inventory` and uses it to update a row in a Google Sheet, or sends a formatted summary to a Slack channel. The Nearblocks tools become the first link in a much longer chain. Because LangChain is framework-agnostic, you can mix and match. An agent could use `get_token_list` to find popular tokens, then query a completely different database for market sentiment on those tokens, and finally make a decision. It turns blockchain data from a siloed resource into an integrated part of your agent's world.

Setup guide

Set up Nearblocks (Near Blockchain Explorer API) MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Nearblocks (Near Blockchain Explorer API) tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "nearblocks-near-blockchain-explorer-api-mcp": {
        "transport": "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,
    )
    result = await agent.ainvoke({
        "messages": "List recent Nearblocks (Near Blockchain Explorer API) transactions"
    })
    print(result["messages"][-1].content)

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Common questions about Nearblocks (Near Blockchain Explorer API) MCP in LangChain

First, install the `langchain-mcp-adapters` package. Then, instantiate the `MultiServerMCPClient` with your Vinkius endpoint. Calling `client.get_tools()` returns a list of functions you can pass directly to your agent's constructor.

Yes. Since you're using LangChain, every tool call, including its inputs and outputs, is automatically captured by LangSmith. This lets you debug exactly how your agent is using tools like `get_account_transactions` and see the data it gets back.

You can build agents that perform on-chain research. For example, an agent could start with `get_recent_transactions`, identify interesting accounts, and then recursively use `get_account_details` and `get_account_tokens` to build a profile of on-chain activity.

No, LangChain doesn't impose a limit. You could create a complex chain that uses all 11 tools, like starting with `get_network_stats`, then finding a block with `get_latest_blocks`, and drilling all the way down to `get_transaction_details`.

This server only queries public Near blockchain data, such as transaction histories and token balances. Your Vinkius endpoint token authenticates your request, and all operations happen in an ephemeral, zero-trust sandbox. The underlying data is public, but your specific queries are private.

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