How to Use the Estimote MCP in AutoGen
Orchestrate multi-agent debates in AutoGen to manage, configure, and optimize your Estimote beacon fleet safely.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Estimote MCP to AutoGen
Create your Vinkius account to connect Estimote 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.
Let AutoGen agents negotiate fleet updates
The `update_beacon_settings` and `list_beacon_devices` tools allow your AutoGen agents to collaborate on hardware configuration changes. A performance-focused agent might try to increase the advertising interval, while a battery-monitoring agent argues to preserve power based on current levels. These agents debate the trade-offs in an open chat window before applying any changes to the cloud shadow. You get optimal configuration settings that balance responsiveness against physical battery constraints without manual calculations.
Automate hardware decommissioning through consensus
The `remove_beacon_device` and `list_physical_locations` tools are managed by AutoGen agents to clean up inactive hardware safely. Since deleting a beacon is permanent, a security agent verifies that the device is actually offline before allowing the removal tool to run. If the location coordinates mismatch or a beacon still shows active telemetry, the audit agent blocks the command. The agents present their reasoning in the conversation log, ensuring you never accidentally delete active hardware from your fleet.
Coordinate multi-site deployments autonomously
The `create_physical_location` and `assign_tag_to_beacon` tools enable AutoGen agents to provision new venues and assign hardware tags systematically. One agent parses the deployment manifest to register the site, while a second agent maps the physical MAC addresses to that location. This multi-agent setup ensures that tag naming conventions are strictly enforced across your entire organization. If an agent tries to use an invalid tag format, the validator agent rejects the proposal and requests a correction before the tool is executed.
Set up Estimote 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 Estimote 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="Estimote_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Estimote 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="Estimote_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Estimote 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 Estimote. 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 Estimote MCP in AutoGen
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