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Baserow MCP Server for LangChainGive LangChain instant access to 9 tools to Create Row, Delete Row, Get Row, and more

Built by Vinkius GDPR 9 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Baserow 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 App Connector for LangChain

The Baserow app connector for LangChain is a standout in the Developer Tools category — giving your AI agent 9 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

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({
        "baserow-alternative": {
            "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 Baserow, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())
Baserow
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 Baserow MCP Server

Connect your Baserow account to any AI agent and take full control of your no-code relational databases and automated data management workflows through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Baserow through native MCP adapters. Connect 9 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

  • Workspace & Database Orchestration — List and monitor your entire Baserow ecosystem programmatically, from high-level workspaces to individual database applications
  • Schema Intelligence — Access and manage tables and fields within your databases to maintain a perfectly coordinated high-fidelity data structure in real-time
  • Row Lifecycle Management — Programmatically list, create, update, and delete rows in any table, retrieving detailed high-fidelity records using custom field names
  • Search & Discovery — Use semantic keywords to search for specific records across your tables to maintain a perfectly coordinated digital ledger
  • Infrastructure Monitoring — Retrieve metadata for database tokens and verify account-level permissions directly through your agent for instant reporting

The Baserow MCP Server exposes 9 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.

All 9 Baserow tools available for LangChain

When LangChain connects to Baserow through Vinkius, your AI agent gets direct access to every tool listed below — spanning no-code, relational-database, data-schema, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

create_row

Provide data as a JSON string of field names and values. Create a new row in a table

delete_row

Delete a specific row

get_row

Get details for a specific row

list_applications

List all Baserow applications (databases)

list_fields

List fields in a table

list_rows

Supports search and pagination. List rows in a table

list_tables

List tables in a database

list_workspaces

List all Baserow workspaces

update_row

Provide data as a JSON string. Update an existing row

Connect Baserow to LangChain via MCP

Follow these steps to wire Baserow into LangChain. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save the code and run python agent.py
04

Explore tools

The agent discovers 9 tools from Baserow via MCP

Why Use LangChain with the Baserow MCP Server

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

01

The largest ecosystem of integrations, chains, and agents. combine Baserow MCP tools with 500+ LangChain components

02

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

03

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

04

Memory and conversation persistence let agents maintain context across Baserow queries for multi-turn workflows

Baserow + LangChain Use Cases

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

01

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

02

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

03

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

04

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

Example Prompts for Baserow in LangChain

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

01

"List all active database applications in my Baserow account."

02

"Show the records in table ID '456' from the 'Customer CRM' database."

03

"Search for 'John Doe' in table '456'."

Troubleshooting Baserow MCP Server with LangChain

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

01

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Baserow + LangChain FAQ

Common questions about integrating Baserow MCP Server with LangChain.

01

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.
02

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.
03

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.