SurrealDB MCP Server for LangChainGive LangChain instant access to 16 tools to Create Record, Create Specific Record, Delete All, and more

Name: SurrealDB
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 SurrealDB 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 for LangChain

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The SurrealDB MCP Server for LangChain is a standout in the Databases category — giving your AI agent 16 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

Claude

ChatGPT

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VS Code

JetBrains

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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({
        "surrealdb": {
            "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 SurrealDB, 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 SurrealDB MCP Server

Connect your SurrealDB database to any AI agent and take full control of your data layer through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with SurrealDB through native MCP adapters. Connect 16 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

SurrealQL Execution — Run raw SurrealQL statements using the execute_sql tool for complex queries and logic.
Record Management — Create, update, and modify records in specific tables with tools like create_record, update_record, or modify_record.
Table Operations — Quickly select_all or delete_all records from a target table to manage your data at scale.
Health Monitoring — Check server status and health metrics using get_status and get_health to ensure uptime.
Data Portability — Use import_sql and export_data to move information in and out of your instance seamlessly.

The SurrealDB MCP Server exposes 16 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 16 SurrealDB tools available for LangChain

When LangChain connects to SurrealDB through Vinkius, your AI agent gets direct access to every tool listed below — spanning multi-model, surrealql, graph-database, 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.

create

Create record on SurrealDB

Create a record with a random ID

create

Create specific record on SurrealDB

Create a specific record

delete

Delete all on SurrealDB

Delete all records in a table

delete

Delete record on SurrealDB

Delete a specific record

execute

Execute sql on SurrealDB

Can pass variables via URL query parameters. Execute SurrealQL statements

export

Export data on SurrealDB

Export data

get

Get health on SurrealDB

Check SurrealDB health

get

Get status on SurrealDB

Check SurrealDB web server status

get

Get version on SurrealDB

Get SurrealDB version

import

Import sql on SurrealDB

Import SurrealQL queries

modify

Modify all on SurrealDB

Modify all records in a table (Merge)

modify

Modify record on SurrealDB

Modify a specific record (Merge)

select

Select all on SurrealDB

Select all records in a table

select

Select record on SurrealDB

Select a specific record

update

Update all on SurrealDB

Update all records in a table

update

Update record on SurrealDB

Update a specific record

Connect SurrealDB to LangChain via MCP

Follow these steps to wire SurrealDB 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 16 tools from SurrealDB via MCP

Why Use LangChain with the SurrealDB MCP Server

LangChain provides unique advantages when paired with SurrealDB through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine SurrealDB 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 SurrealDB queries for multi-turn workflows

SurrealDB + LangChain Use Cases

Practical scenarios where LangChain combined with the SurrealDB MCP Server delivers measurable value.

RAG with live data: combine SurrealDB tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query SurrealDB, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain SurrealDB tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every SurrealDB tool call, measure latency, and optimize your agent's performance

Example Prompts for SurrealDB in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with SurrealDB immediately.

"Check the health and version of my SurrealDB server."

"Select all records from the 'users' table."

"Execute a SurrealQL query to find all posts where status is 'published'."

Troubleshooting SurrealDB MCP Server with LangChain

Common issues when connecting SurrealDB to LangChain through Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

SurrealDB + LangChain FAQ

Common questions about integrating SurrealDB 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.