Routific MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Routific 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({
"routific": {
"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 Routific, 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 Routific MCP Server
Connect your conversational assistant directly to Routific, a premier logistics scaling platform. This integration seamlessly turns your AI into an advanced delivery dispatcher, allowing you to build multi-stop route solutions securely, manage outstanding delivery jobs, and proactively push dispatch tasks directly to drivers' mobile apps natively in one window.
LangChain's ecosystem of 500+ components combines seamlessly with Routific 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.
What you can do
- Automate VRP Computations — Submit basic logistics parameters (
solve_standalone_vrp) or delegate massive multi-depot configurations organically (solve_async_vrp_long) and query asynchronous status returns effortlessly (poll_async_solution). - Control Saas Delivery Jobs — Tell the AI to actively audit outstanding orders (
list_platform_jobs) or create fresh delivery injections accurately handling order constraints and priorities directly into the system (create_saas_job,update_saas_job). - Assemble & Publish Timelines — Review the resulting stop-by-stop ETAs securely calculated by algorithms natively inside the interface (
get_route_timeline). Once completely satisfied, simply push the finalized route natively to the targeted driver's phone with an organic command (publish_route_to_driver).
The Routific 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 Routific to LangChain via MCP
Follow these steps to integrate the Routific 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 Routific via MCP
Why Use LangChain with the Routific MCP Server
LangChain provides unique advantages when paired with Routific through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Routific 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 Routific queries for multi-turn workflows
Routific + LangChain Use Cases
Practical scenarios where LangChain combined with the Routific MCP Server delivers measurable value.
RAG with live data: combine Routific tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Routific, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Routific tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Routific tool call, measure latency, and optimize your agent's performance
Routific MCP Tools for LangChain (10)
These 10 tools become available when you connect Routific to LangChain via MCP:
cancel_saas_job
This action is irreversible. Cancels and deletes a delivery job from the platform
create_platform_route
Creates a new route plan in the platform
create_saas_job
Provide a JSON object with order details. Creates a new delivery job in the platform
get_route_timeline
Retrieves the stop-by-stop timeline for a route
list_platform_jobs
Lists all delivery jobs in the Routific platform
poll_async_solution
Polls the status of an asynchronous VRP job
publish_route_to_driver
Publishes a route to the driver's mobile app
solve_async_vrp_long
Returns a job ID for polling. Submits a large Vehicle Routing Problem for asynchronous solving
solve_standalone_vrp
Provide a JSON object with visits, fleet, and options. Solves a standalone Vehicle Routing Problem synchronously
update_saas_job
Updates an existing delivery job
Example Prompts for Routific in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Routific immediately.
"List all current delivery jobs pending in the platform right now."
"Generate a standalone route resolving 4 pending visits."
"Publish the finalized route to the designated driver's mobile app."
Troubleshooting Routific MCP Server with LangChain
Common issues when connecting Routific to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersRoutific + LangChain FAQ
Common questions about integrating Routific 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 Routific 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 Routific to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.