How to Use the Estimote MCP in CrewAI
Deploy CrewAI agent teams to monitor telemetry, manage tags, and optimize physical Estimote fleets via this MCP server.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Estimote MCP to CrewAI
Create your Vinkius account to connect Estimote to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Coordinate Multi-Agent Fleet Inspections
`list_beacon_devices` allows your specialized CrewAI research agent to inventory every physical beacon registered to your account. The agent pulls MAC addresses, battery status, and firmware versions, then hands the data to an analyst agent. The analyst agent checks for outdated firmware or low batteries, while a coordination agent schedules maintenance. This division of labor keeps your physical deployment healthy without manual human intervention.
Automate Physical Location Deployments
`create_physical_location` registers your new retail venues using a specialized setup agent. Once the location is created, a second agent runs `list_physical_locations` to verify the geographic coordinates and site name in the database. This team of agents then runs `assign_tag_to_beacon` to group the hardware by store section. This automated pipeline ensures your physical locations are correctly mapped and tagged the moment your field team installs the devices.
Optimize Transmit Power via MCP Server
`update_beacon_settings` queues changes to broadcasting power and advertising intervals based on recommendations from your optimization agent. The agent analyzes hardware telemetry to find the sweet spot between battery life and signal range. To avoid draining the physical batteries, a supervisor agent monitors this process and blocks excessive updates. This keeps your hardware running longer while maintaining accurate proximity detection on the sales floor.
Set up Estimote MCP in CrewAI
Prerequisites
- Python 3.10+ installed
-
crewaipackage (pip install crewai) - Active Vinkius subscription with a valid endpoint token
- 1
Install CrewAI
Run
pip install crewaito install the framework. MCP support is built-in via themcpsparameter. - 2
Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the
mcpslist. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically. - 3
Kick off your crew
Create a
Crewwith your agent and tasks. Callcrew.kickoff()— the agent will automatically invoke Estimote tools as needed.
from crewai import Agent, Task, Crew
agent = Agent(
role="Estimote Analyst",
goal="Access and analyze Estimote data via MCP.",
backstory="Expert analyst with direct Estimote access.",
mcps=[
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
],
)
task = Task(
description="List recent Estimote transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) Prerequisites
- Python 3.10+ installed
-
crewai+crewai-toolspackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
pip install crewai crewai-tools. TheMCPServerAdapterhandles lifecycle management and tool conversion. - 2
Connect with MCPServerAdapter
Use
MCPServerAdapteras a context manager withSseServerParameterspointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle. - 3
Assign tools and run
Pass the returned
mcp_toolsto your agent'stoolsparameter. The adapter converts MCP tools to nativeBaseToolobjects compatible with all CrewAI agents.
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters
server_params = SseServerParameters(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
with MCPServerAdapter(server_params) as mcp_tools:
agent = Agent(
role="Estimote Analyst",
goal="Access and analyze Estimote data via MCP.",
backstory="Expert analyst with direct Estimote access.",
tools=mcp_tools,
)
task = Task(
description="List recent Estimote transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) 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.
Why Choose Vinkius
Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.
Real-time monitoring
Live
visibility into every interaction
Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.
Built-in savings
60%
lower AI costs
Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.
Single dashboard
One
place for every integration
Every tool your AI connects to, managed from a single screen. One account, complete control.
Common questions about Estimote MCP in CrewAI
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