How to Use the Nominatim MCP in CrewAI

Q: How does CrewAI handle a down Nominatim MCP Server?

Your monitor agent can call the getstatus tool to check the server latency. If the service is unresponsive, the crew can pivot to local cached data or pause execution.

Coordinate multi-agent teams to analyze maps and verify addresses using the Nominatim MCP Server in CrewAI.

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Connect Nominatim MCP to CrewAI

Create your Vinkius account to connect Nominatim 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.

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Setup Nominatim with CrewAI

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Perplexity

Delegate spatial lookups to specialized CrewAI agents

The `search` tool allows a researcher agent to resolve raw addresses into coordinates without manual code. This MCP Server gives your CrewAI team the ability to verify regional details before passing data to analytical agents. Your agents coordinate sequentially, meaning one agent finds the coordinates while another evaluates the surrounding area. This workflow eliminates the need for expensive proprietary mapping APIs.

Extract deep regional hierarchies automatically

The `get_details` tool extracts the full parent place hierarchy, bounding boxes, and linked Wikidata for any location. Within a CrewAI team, a specialized analysis agent uses this tool to classify locations by their administrative importance. Having access to parent hierarchies lets your agents understand if a specific street falls inside a target delivery zone. They make smarter routing decisions based on open-source geographic data.

Resolve coordinates to street addresses autonomously

The `reverse_geocode` tool converts raw coordinates into structured address objects. Your CrewAI agent uses this tool to identify the closest postal address for incoming GPS telemetry logs. By adjusting the zoom parameter, the agent controls whether it receives a precise building number or just the county name. This flexibility keeps your autonomous operations highly context-aware.

Setup guide

Set up Nominatim MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. 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 Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Nominatim tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Nominatim Analyst",
    goal="Access and analyze Nominatim data via MCP.",
    backstory="Expert analyst with direct Nominatim access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Nominatim transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

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="Nominatim Analyst",
        goal="Access and analyze Nominatim data via MCP.",
        backstory="Expert analyst with direct Nominatim access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Nominatim transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Nominatim. 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 Nominatim MCP in CrewAI

You should configure your CrewAI manager agent to serialize tasks that call the search tool. This sequential execution maintains the required one-second delay between queries.

Yes. The agent passes a comma-separated list of formatted IDs to the lookup_osm tool to fetch multiple nodes or ways in a single execution step.

Your monitor agent can call the get_status tool to check the server latency. If the service is unresponsive, the crew can pivot to local cached data or pause execution.

It requires no API keys and accesses the complete OpenStreetMap database. Your CrewAI agents get rich metadata like Wikidata links and place ranks completely free of licensing costs.

The server processes only the specific coordinates and address text required for geocoding. All data transit occurs over encrypted channels directly to the OSM Nominatim servers, with no intermediate data logging.

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