How to Use the Baserow MCP in AutoGen
Let your AutoGen agents debate and collaborate on managing your Baserow databases.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Baserow MCP to AutoGen
Create your Vinkius account to connect Baserow to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Consensus-Driven Database Changes
This is for when you can't afford mistakes. Instead of one agent making a blind change, an agent can propose an update with `update_row`. A second "auditor" agent can then use `get_row` to fetch the current state and challenge the proposal if it's incorrect. The agents converse until they reach an agreement. Only then is the final tool call executed. This is how you use AutoGen to put a review process on critical data changes, all done automatically.
Multi-Agent Data Exploration
Set up a team of agents to map out your data. A "scout" agent can use `list_workspaces` and `list_applications` to find all databases. It passes that list to a "mapper" agent, which then uses `list_tables` and `list_fields` to document the schema of each one. This collaborative approach builds a complete picture of your Baserow environment. The final report is a product of their conversation, not just a simple data dump. This is how you use this MCP server to automate complex discovery tasks.
Build Specialist Agents with this AutoGen MCP Server
Create agents with specific jobs. A "writer" agent is only allowed to use `create_row`. A "reader" agent can only use `list_rows` and `get_row`. An "admin" agent gets access to everything, including `delete_row`. AutoGen's framework lets you define these roles and their allowed tools. When a task comes in, the agents collaborate, each contributing based on their permissions. The writer can't delete data; it has to ask the admin agent for help, providing a justification.
Set up Baserow MCP in AutoGen
Prerequisites
- Python 3.10+ installed
-
autogen-ext[mcp]package - Active Vinkius subscription with a valid endpoint token
- 1
Install AutoGen with MCP
Run
pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includesmcp_server_toolsfor stateless tool access. - 2
Fetch tools from the MCP
Call
mcp_server_tools(SseServerParams(url=...))with your Vinkius endpoint. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. - 3
Run your agent
Pass the tools to
AssistantAgentand callagent.run(). The agent invokes Baserow tools and returns structured results.
from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
server_params = SseServerParams(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
tools = await mcp_server_tools(server_params)
agent = AssistantAgent(
name="Baserow_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Baserow data")
print(result.messages[-1].content) Prerequisites
- Python 3.10+ installed
-
autogen-ext[mcp]+autogen-agentchat - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Same packages as above.
McpWorkbenchis ideal when your agent needs stateful sessions across multiple tool calls. - 2
Use McpWorkbench as context manager
Wrap your agent in
async with McpWorkbench(...)to maintain shared state and resources. The workbench manages the full MCP session lifecycle. - 3
Run with workbench
Pass
workbench=workbenchto your agent. State is preserved across multiple tool calls within the same session.
from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
server_params = SseServerParams(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
async with McpWorkbench(server_params) as workbench:
agent = AssistantAgent(
name="Baserow_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Baserow data")
print(result.messages[-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Baserow. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Common questions about Baserow MCP in AutoGen
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