Can the AI find out if a specific property is inside a flood zone?

Yes. First the AI uses `geocode_address` to find the exact Latitude/Longitude of the building's rooftop. Then it feeds those coordinates into `enrich_flood_risk` to extract the strict FEMA designation naturally.

How accurately does verify_address standardize locations?

Very accurately. It connects to native postal services (like USPS and Royal Mail) to autocorrect misspellings, adjust zip codes, and flag impossible addresses before they reach your logistics layer.

Do I need two separate keys to use this?

Yes. Precisely Developer APIs use robust OAuth workflows. You must supply both the individual API Key (Consumer Key) and the API Secret. The MCP server handles token exchanging for you internally.

Precisely MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: Precisely
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Precisely through the Vinkius — pass the Edge URL in the `mcps` parameter and every Precisely tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Precisely Specialist",
    goal="Help users interact with Precisely effectively",
    backstory=(
        "You are an expert at leveraging Precisely 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 Precisely "
        "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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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Precisely MCP Server

Fuse the Precisely geospatial intelligence network directly into your AI workflows, enabling your agents to accurately pinpoint addresses globally, extract demographics, and evaluate location-based risks with unparalleled precision.

When paired with CrewAI, Precisely becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Precisely 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

Geocoding & Autocompletion — Supply partial strings and tell the AI to resolve absolute Coordinates globally (geocode_address, autocomplete_address)
Risk Assessment — Submit coordinates to instantly read FEMA flood zones or comparative crime metrics for that property (enrich_flood_risk, enrich_crime_risk)
Tax Boundaries — Ask the AI to parse the exact Local Sales Tax jurisdiction applying strictly to that rooftop coordinate (get_local_tax)
Deep Enrichment — Convert standard US Addresses into comprehensive property records including square footage and household socioeconomic segments

The Precisely 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 Precisely to CrewAI via MCP

Follow these steps to integrate the Precisely 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 Precisely

Why Use CrewAI with the Precisely MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Precisely 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

Precisely + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Precisely MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Precisely 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 Precisely, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Precisely 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 Precisely against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Precisely MCP Tools for CrewAI (10)

These 10 tools become available when you connect Precisely to CrewAI via MCP:

autocomplete_address

Returns up to 10 candidate addresses ranked by relevance. Designed for keystroke-by-keystroke usage in address input forms. Provide real-time address suggestions as users type using the Precisely Typeahead Autocomplete API, drawing from a comprehensive global address database to accelerate form completion and reduce entry errors

enrich_crime_risk

Returns crime indices normalized to a national average of 100 — values above 100 indicate higher-than-average risk. Assess the crime risk index for a specific location using the Precisely Risks API, returning normalized risk scores across categories like burglary, assault, vehicle theft, and overall crime relative to national averages

enrich_demographics

Returns rich socio-economic profiles for the census block or postal zone containing the coordinates. Retrieve detailed demographic segmentation data for a geographic coordinate using the Precisely Demographics API, including household income brackets, population density, education levels, age distribution, and consumer spending patterns

enrich_flood_risk

Returns flood zone classification (A, AE, X, V), base flood elevation, and risk index. Primarily covers US territories with FEMA data. Evaluate flood risk exposure for a specific location using the Precisely Environmental Risks API, returning FEMA flood zone designations, proximity to water bodies, elevation data, and flood risk scores

geocode_address

precisely.com. The API returns a ranked list of candidates with latitude, longitude, precision code, and match confidence. Always pass the most complete address string available to maximize match quality. The response includes PrecisionCode indicating match depth (S8 = rooftop, S5 = street-level). Forward-geocode a full or partial address string into geographic coordinates using the Precisely Geocoding API v1, which resolves against a world-class global address reference database covering 250+ countries and territories

get_local_tax

Returns the combined tax rate and individual components (state, county, city, special district). Determine the applicable sales tax rate and tax jurisdiction for a geographic location using the Precisely Local Tax API, resolving complex overlapping US tax jurisdictions down to the rooftop level

get_property_info

Returns a rich property record sourced from county assessor databases. Coverage is US-only. Retrieve comprehensive property attribute data for a US address using the Precisely Property API v2, including lot size, building square footage, year built, number of bedrooms/bathrooms, assessed value, and ownership information

get_timezone

Returns the IANA timezone identifier (e.g. America/New_York), current UTC offset, and DST status. Resolve the timezone and current UTC offset for any geographic coordinate using the Precisely Timezone API, accounting for daylight saving time transitions and political boundary changes

reverse_geocode

Note the parameter order: x = longitude, y = latitude. Returns the closest matching address with full components (street, city, state, postal code, country). Convert geographic coordinates (latitude/longitude) back into a structured postal address using the Precisely Reverse Geocoding API, resolving the nearest rooftop-level address from the global reference database

verify_address

Returns a verified, standardized address with a verification status indicating if the address is deliverable, if components were corrected, or if the address is invalid. Validate and standardize a postal address against authoritative reference datasets using the Precisely Address Verification API, returning USPS/Royal Mail/local postal authority standardized formatting and deliverability status

Example Prompts for Precisely in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Precisely immediately.

"What is the exact sales tax for an e-commerce order delivered to '1 Market St, San Francisco, CA'?"

"Check the crime risk around the latitude 40.7128 and longitude -74.0060 relative to the national average."

"Can you verify if '350 5th Ave New York 10118' is a real deliverable address? If yes, give me its timezone."

Troubleshooting Precisely MCP Server with CrewAI

Common issues when connecting Precisely 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.

Precisely + CrewAI FAQ

Common questions about integrating Precisely 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.