Xata (Serverless DB) MCP Server for LangChainGive LangChain instant access to 30 tools to Create Branch, Create Organization, Create Project, and more
LangChain is the leading Python framework for composable LLM applications. Connect Xata (Serverless DB) 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
The Xata (Serverless DB) MCP Server for LangChain is a standout in the Databases category — giving your AI agent 30 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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({
"xata-serverless-db": {
"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 Xata (Serverless DB), 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 Xata (Serverless DB) MCP Server
Connect your Xata account to any AI agent to manage your serverless data infrastructure through natural conversation. Xata combines the power of a relational database with the ease of use of a spreadsheet, all accessible via this MCP server.
LangChain's ecosystem of 500+ components combines seamlessly with Xata (Serverless DB) through native MCP adapters. Connect 30 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
- Organization Management — List, create, and update organizations and manage team members or invitations using
list_organizationsandlist_members. - Project & Branch Control — Create and manage projects and database branches across different regions with
create_projectandcreate_branch. - SQL Execution — Run SQL queries or batches directly against your database branches to fetch or manipulate data using
execute_sql. - Infrastructure Insights — Retrieve branch metrics, credentials, and project limits to monitor your serverless environment with
get_branch_metricsandget_project_limits.
The Xata (Serverless DB) MCP Server exposes 30 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 30 Xata (Serverless DB) tools available for LangChain
When LangChain connects to Xata (Serverless DB) through Vinkius, your AI agent gets direct access to every tool listed below — spanning serverless, sql, database-migration, 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 branch on Xata (Serverless DB)
Create a new database branch
Create organization on Xata (Serverless DB)
Create a new organization
Create project on Xata (Serverless DB)
Create a new project
Delete branch on Xata (Serverless DB)
Delete a branch
Delete invitation on Xata (Serverless DB)
Delete an organization invitation
Delete project on Xata (Serverless DB)
Delete a project
Execute sql on Xata (Serverless DB)
Execute a SQL query against a branch
Execute sql batch on Xata (Serverless DB)
Execute a batch of SQL queries in a single transaction
Get branch on Xata (Serverless DB)
Get branch details
Get branch credentials on Xata (Serverless DB)
Retrieve branch credentials
Get branch metrics on Xata (Serverless DB)
Retrieve branch metrics
Get organization on Xata (Serverless DB)
Get organization details
Get project on Xata (Serverless DB)
Get project details
Get project limits on Xata (Serverless DB)
Get resource limits for projects
List branches on Xata (Serverless DB)
List all branches in a project
List images on Xata (Serverless DB)
List available images
List instance types on Xata (Serverless DB)
List available instance types for a region
List invitations on Xata (Serverless DB)
List organization invitations
List members on Xata (Serverless DB)
List organization members
List organizations on Xata (Serverless DB)
List all organizations
List projects on Xata (Serverless DB)
List all projects in an organization
List regions on Xata (Serverless DB)
List available regions
Remove member on Xata (Serverless DB)
Remove a member from an organization
Request organization deletion on Xata (Serverless DB)
Request organization deletion
Resend invitation on Xata (Serverless DB)
Resend an organization invitation
Rotate branch credentials on Xata (Serverless DB)
Rotate branch credentials
Send invitation on Xata (Serverless DB)
Send an invitation to join an organization
Update branch on Xata (Serverless DB)
Update branch details
Update organization on Xata (Serverless DB)
Update organization details
Update project on Xata (Serverless DB)
Update project details
Connect Xata (Serverless DB) to LangChain via MCP
Follow these steps to wire Xata (Serverless DB) into LangChain. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.
Install dependencies
pip install langchain langchain-mcp-adapters langgraph langchain-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
python agent.pyExplore tools
Why Use LangChain with the Xata (Serverless DB) MCP Server
LangChain provides unique advantages when paired with Xata (Serverless DB) through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Xata (Serverless DB) 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 Xata (Serverless DB) queries for multi-turn workflows
Xata (Serverless DB) + LangChain Use Cases
Practical scenarios where LangChain combined with the Xata (Serverless DB) MCP Server delivers measurable value.
RAG with live data: combine Xata (Serverless DB) tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Xata (Serverless DB), synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Xata (Serverless DB) tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Xata (Serverless DB) tool call, measure latency, and optimize your agent's performance
Example Prompts for Xata (Serverless DB) in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Xata (Serverless DB) immediately.
"List all my Xata organizations and their details."
"Show me all branches for project 'my-database' in organization 'org-123'."
"Execute SQL: SELECT name, email FROM users WHERE active = true LIMIT 5 on the main branch."
Troubleshooting Xata (Serverless DB) MCP Server with LangChain
Common issues when connecting Xata (Serverless DB) to LangChain through Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersXata (Serverless DB) + LangChain FAQ
Common questions about integrating Xata (Serverless DB) 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?
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