How high is the resolution of Nearmap imagery compared to standard satellite maps?

Nearmap provides high-resolution aerial imagery at sub-15cm (approx. 6 inch) Ground Sample Distance (GSD). This is significantly sharper than typical satellite imagery (usually 30cm-50cm), allowing your agent to identify fine site details like roof vents, pavement cracks, or pool conditions.

Can my agent automatically detect solar panels or swimming pools on a property?

Yes. Use the `get_ai_detected_features` tool. Nearmap's AI analyzes recent surveys to return vector geometries for specific feature classes like 'Solar Panels' or 'Swimming Pools', including confidence thresholds and area measurements.

What is 'Oblique' imagery and how do I access it through the agent?

Oblique imagery is captured at a 45-degree angle rather than straight down. Use the `get_oblique_tile` tool and specify a direction (North, South, East, West). This allows your agent to audit building facades, structural heights, and side-view property details.

Nearmap (High-Res Aerial Imagery & AI) MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: Nearmap (High-Res Aerial Imagery & AI)
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Nearmap (High-Res Aerial Imagery & AI) through the Vinkius — pass the Edge URL in the `mcps` parameter and every Nearmap (High-Res Aerial Imagery & AI) tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Nearmap (High-Res Aerial Imagery & AI) Specialist",
    goal="Help users interact with Nearmap (High-Res Aerial Imagery & AI) effectively",
    backstory=(
        "You are an expert at leveraging Nearmap (High-Res Aerial Imagery & AI) tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token — get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Nearmap (High-Res Aerial Imagery & AI) "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

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

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About Nearmap (High-Res Aerial Imagery & AI) MCP Server

Connect your Nearmap account to any AI agent and take full control of world-class high-resolution aerial imagery, geospatial AI insights, and topographic surface models through natural conversation.

When paired with CrewAI, Nearmap (High-Res Aerial Imagery & AI) becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Nearmap (High-Res Aerial Imagery & AI) tools autonomously — one agent queries data, another analyzes results, a third compiles reports — all orchestrated through the Vinkius with zero configuration overhead.

What you can do

Aerial Orchestration — Retrieve sub-15cm resolution vertical (nadir) imagery tiles using Web Mercator coordinates to verify site conditions directly from your agent
AI Feature Extraction — Automatically detect and extract vector geometries for buildings, swimming pools, solar panels, and vegetation within specific geographic radii
Perspective Oblique Imagery — Access 3D-angled imagery from North, South, East, and West viewpoints to audit structural facades and building heights securely
Coverage & Survey Audit — Verify imagery availability across specific points or complex polygons and retrieve chronological survey dates to track site changes over time
Topographic Modeling — Extract Digital Surface Model (DSM) elevation tiles to analyze terrain peaks, building heights, and surface volumes natively within your workspace
True Ortho Visualization — Retrieve geometric lean-corrected top-down layers providing zero parallax alignments for perfect geospatial mapping and precision measurement
Survey Metadata — Query explicit flight parameters including Ground Sample Distance (GSD) and optical capture details for any specific aerial flyover

The Nearmap (High-Res Aerial Imagery & AI) MCP Server exposes 10 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Nearmap (High-Res Aerial Imagery & AI) to CrewAI via MCP

Follow these steps to integrate the Nearmap (High-Res Aerial Imagery & AI) MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py — CrewAI auto-discovers 10 tools from Nearmap (High-Res Aerial Imagery & AI)

Why Use CrewAI with the Nearmap (High-Res Aerial Imagery & AI) MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Nearmap (High-Res Aerial Imagery & AI) through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles — one agent researches, another analyzes, a third generates reports — each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass the Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Nearmap (High-Res Aerial Imagery & AI) + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Nearmap (High-Res Aerial Imagery & AI) MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Nearmap (High-Res Aerial Imagery & AI) for raw data, then a second analyst agent cross-references findings and flags anomalies — all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Nearmap (High-Res Aerial Imagery & AI), analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Nearmap (High-Res Aerial Imagery & AI) tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Nearmap (High-Res Aerial Imagery & AI) against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Nearmap (High-Res Aerial Imagery & AI) MCP Tools for CrewAI (10)

These 10 tools become available when you connect Nearmap (High-Res Aerial Imagery & AI) to CrewAI via MCP:

check_coverage_point

Verify Nearmap capture boundaries matching geospatial point resolving temporal history arrays

check_coverage_polygon

Verify internal aerial survey boundary masks checking imagery intersections across mapped polygons

get_ai_detected_features

Extract vector geometry parsing buildings, pools, vegetation, solar panels via automated CV features bounds

get_dsm_elevation_tile

Extract pixelated Digital Surface Model mapping topographic terrain and building peak heights

get_oblique_tile

Retrieve oblique perspective 3D-angled imagery tiles pointing North, South, East, West locating structural targets

get_survey_metadata

Query explicitly bounded survey parameters finding GSD resolutions finding optical flight details

get_true_ortho_tile

Retrieve lean-corrected true geometric top-down bounding layers capturing zero parallax alignments

get_vertical_tile

Retrieve high-resolution vertical static nadir aerial imagery tiles tracking captured boundaries

list_ai_feature_classes

Lookup all internal AI category taxonomies evaluating computer vision mappings detecting roof arrays

list_survey_dates

Iterate chronological availability boundaries mapping all temporal captures crossing target nodes

Example Prompts for Nearmap (High-Res Aerial Imagery & AI) in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Nearmap (High-Res Aerial Imagery & AI) immediately.

"Get the latest high-res vertical imagery for coordinates '34.0522,-118.2437'"

"Detect all solar panels within a 100m radius of this point: [lat,lon]"

"Show me the oblique view from the North for this building coordinate"

Troubleshooting Nearmap (High-Res Aerial Imagery & AI) MCP Server with CrewAI

Common issues when connecting Nearmap (High-Res Aerial Imagery & AI) to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts — check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

The Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Nearmap (High-Res Aerial Imagery & AI) + CrewAI FAQ

Common questions about integrating Nearmap (High-Res Aerial Imagery & AI) MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily — when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.