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How to Use the Towio MCP in LlamaIndex

Query past tow operations with LlamaIndex's knowledge-grounded search.

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LlamaIndex

Connect Towio MCP to LlamaIndex

Create your Vinkius account to connect Towio to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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MCP Server for Towio Knowledge Indexing

When you run `list_delivery_documents`, the output becomes part of your searchable index. You can later query this index to recall specific manifest details from past roadside assistance jobs.

Retrieving Employee Data with LlamaIndex

The `list_employees` tool feeds data into your knowledge base. Instead of just listing employees, you can ask complex questions like 'Who managed the dispatch on Project X?' and get a grounded answer.

Analyzing Towio Tasks with LlamaIndex

You use `list_tasks` to retrieve current action items. Indexing this data lets you build RAG applications that surface historical context—for example, 'What were the common tasks for a failed dispatch in Q3?'

Setup guide

Set up Towio MCP in LlamaIndex

Prerequisites

  • Python 3.10+ installed
  • llama-index-tools-mcp package
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Install dependencies

    Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.

  2. 2

    Connect with BasicMCPClient

    Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.

  3. 3

    Convert to LlamaIndex tools

    Call mcp_tool_spec.to_tool_list_async() to convert all Towio MCP tools into native FunctionTool objects that any LlamaIndex agent can use.

  4. 4

    Run with any LLM

    Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Towio tools.",
)
response = await agent.run("List recent Towio data")

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Towio. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Towio MCP in LlamaIndex

LlamaIndex indexes the output from tools like `list_tasks`. This means you don't just get a list; you build a searchable record of past service calls and task history.
Yes, the server provides `list_employees`. By indexing this result, you can query specific personnel details or roles from your historical knowledge base.
This MCP Server exposes project lists, task status updates, and employee records. LlamaIndex turns that structured API data into a unified, queryable index for your application.
Absolutely. The `list_delivery_documents` tool sends its results to the knowledge base. You can then search across all historical delivery manifests easily.
The server touches employee records and task details. When building your index, keep in mind that the stored knowledge base contains sensitive information about personnel and job assignments.

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