How do I get an API Key for Gingr?

Log in to Gingr, navigate to Reports & More > Users, edit your user, and look for the 'API Keys' section to generate or copy your key.

Can I create new reservations via the agent?

No, the current Gingr Public API is read-only. This integration is designed for safely retrieving and auditing your existing data.

How do I find my Location ID?

Use the 'list_business_locations' tool. The agent will return all configured locations in your app along with their unique IDs.

Is the Digital Whiteboard data live?

Yes, all data retrieved through the 'get_digital_whiteboard' tool is fetched directly from the Gingr API, reflecting the current state of your facility.

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

Name: Gingr
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Gingr through Vinkius, pass the Edge URL in the `mcps` parameter and every Gingr 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="Gingr Specialist",
    goal="Help users interact with Gingr effectively",
    backstory=(
        "You are an expert at leveraging Gingr 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 Gingr "
        "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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Ed25519Audit chain

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Gingr MCP Server

Connect your Gingr pet care management account to any AI agent to automate your data extraction and customer support workflows through the Model Context Protocol (MCP). Gingr is the leading platform for kennel, daycare, and grooming businesses. This MCP server enables you to retrieve detailed pet owner profiles, track upcoming and past reservations, and monitor real-time facility check-ins directly through natural conversation.

When paired with CrewAI, Gingr becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Gingr tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

Key Features

Owner & Pet Insights — Retrieve complete profile metadata for pet owners using IDs, email addresses, or phone numbers.
Reservation Tracking — List all boarding, daycare, and grooming reservations for any owner, filtered by status (future or currently checked-in).
Digital Whiteboard Oversight — Access 'Back of House' data to see real-time facility activity and room assignments for any location.
Custom Data Discovery — Search across custom metadata fields for both owners and animals to find specific regional or internal attributes.
Facility Transparency — List all business locations and facilities configured in your Gingr app.
Read-only Security — Safely query your pet care database with a secure, read-only integration designed for data visibility.
Real-time Synchronization — Keep your facility operations data accessible to your AI assistant without leaving your primary workspace.

The Gingr 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 Gingr to CrewAI via MCP

Follow these steps to integrate the Gingr 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 Gingr

Why Use CrewAI with the Gingr MCP Server

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

Gingr + CrewAI Use Cases

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

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

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

Gingr MCP Tools for CrewAI (10)

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

find_owner_by_email

Search owner by email

find_owner_by_phone

Search owner by phone

get_digital_whiteboard

View active whiteboard

get_pet_owner_details

Get owner profile

list_active_checkins

List currently checked-in

list_business_locations

List pet care facilities

list_owner_reservations

) for a specific owner. List past/future bookings

search_owner_custom_fields

Search custom owner data

search_pet_custom_fields

Search custom pet data

verify_api_connection

Check connection

Example Prompts for Gingr in CrewAI

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

"Find pet owner details for 'john@email.com'."

"List all future reservations for owner ID '12345'."

"Show me the current digital whiteboard for location '1'."

Troubleshooting Gingr MCP Server with CrewAI

Common issues when connecting Gingr 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

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

Gingr + CrewAI FAQ

Common questions about integrating Gingr 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.