Gingr MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Gingr through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MultiServerMCPClient({
"gingr": {
"transport": "streamable_http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using Gingr, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* 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.
LangChain's ecosystem of 500+ components combines seamlessly with Gingr through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
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 LangChain 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 LangChain via MCP
Follow these steps to integrate the Gingr MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 10 tools from Gingr via MCP
Why Use LangChain with the Gingr MCP Server
LangChain provides unique advantages when paired with Gingr through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Gingr MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across Gingr queries for multi-turn workflows
Gingr + LangChain Use Cases
Practical scenarios where LangChain combined with the Gingr MCP Server delivers measurable value.
RAG with live data: combine Gingr tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Gingr, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Gingr tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Gingr tool call, measure latency, and optimize your agent's performance
Gingr MCP Tools for LangChain (10)
These 10 tools become available when you connect Gingr to LangChain 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 LangChain
Ready-to-use prompts you can give your LangChain 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 LangChain
Common issues when connecting Gingr to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersGingr + LangChain FAQ
Common questions about integrating Gingr MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
Connect Gingr with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Gingr to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.