Routific MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Routific as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Routific. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Routific?"
)
print(response)
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.
LlamaIndex agents combine Routific tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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 LlamaIndex 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 LlamaIndex via MCP
Follow these steps to integrate the Routific MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 10 tools from Routific
Why Use LlamaIndex with the Routific MCP Server
LlamaIndex provides unique advantages when paired with Routific through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Routific tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Routific tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Routific, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Routific tools were called, what data was returned, and how it influenced the final answer
Routific + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Routific MCP Server delivers measurable value.
Hybrid search: combine Routific real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Routific to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Routific for fresh data
Analytical workflows: chain Routific queries with LlamaIndex's data connectors to build multi-source analytical reports
Routific MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Routific to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting Routific to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpRoutific + LlamaIndex FAQ
Common questions about integrating Routific MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
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 LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.