How to Use the Jawg Maps (Location & Routing) MCP in LlamaIndex

Q: How do I configure Jawg Maps (Location & Routing) with LlamaIndex?

Install the tool package using pip install llama-index-tools-mcp. Initialize the BasicMCPClient with your Vinkius MCP endpoint, wrap it in a McpToolSpec, and pass the tools to your FunctionAgent.

Q: Can I index routing results from Jawg Maps (Location & Routing) into LlamaIndex?

Yes, the agent can write the output of calculateroutingline directly into your vector store. This lets you run semantic searches over previously calculated routes to save processing time.

Q: Does Jawg Maps (Location & Routing) support autocomplete lookups in LlamaIndex?

The searchautocomplete tool allows your agent to clean up user input before indexing the location. It resolves messy, partial address strings into clean coordinates. This ensures your vector index stays highly accurate.

Q: Can I restrict place searches to specific countries?

Use searchcountryfilter to force the agent to search only within designated borders. This prevents your index from getting polluted with global address matches that don't apply to your business.

Index real-time spatial data and routing profiles directly into your LlamaIndex vector stores.

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Connect Jawg Maps (Location & Routing) MCP to LlamaIndex

Create your Vinkius account to connect Jawg Maps (Location & Routing) 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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Setup Jawg Maps (Location & Routing) with LlamaIndex

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Index Location Data into LlamaIndex Vector Stores

This MCP server exposes `search_map_places` to let your LlamaIndex agent pull accurate coordinate data and index it for future semantic queries. Instead of relying on static, outdated geographic files, your RAG pipeline queries live spatial data. The agent writes the results directly to your vector database. When you need to retrieve past location queries, the system searches the index instead of calling the API again. This saves on API costs while keeping your application fast. You get grounded answers based on actual geographic coordinates.

Build Searchable Isochrone Profiles

The `calculate_reachability_isochrone` tool generates reachable area data that your agent can index alongside your customer profiles. Your agent queries this index to instantly find which customers fall within a specific delivery window. This removes the need for real-time spatial calculations during high-traffic periods. Your agent uses this MCP server to handle distance-based queries by running `calculate_distance_isochrone` and indexing the resulting boundary coordinates. It builds a searchable knowledge base of delivery zones. Your query engine can then resolve spatial coverage questions without hitting external servers.

Store and Query Terrain Data

Running `get_path_elevation` via our MCP server gives your LlamaIndex agent raw altitude data along any specific path coordinates. The agent indexes these elevation profiles directly into your document store. This allows your system to perform semantic searches on route difficulty and terrain slopes. It pairs this with `calculate_elevation_routing` to build a history of optimized paths. Your agent analyzes these stored routes to find patterns in fuel consumption or travel speed. You turn raw spatial queries into reusable knowledge assets.

Setup guide

Set up Jawg Maps (Location & Routing) MCP in LlamaIndex

Prerequisites

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

1

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

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Jawg Maps (Location & Routing) MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
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 Jawg Maps (Location & Routing) tools.",
)
response = await agent.run("List recent Jawg Maps (Location & Routing) data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Jawg Maps. 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 Jawg Maps (Location & Routing) MCP in LlamaIndex

Install the tool package using `pip install llama-index-tools-mcp`. Initialize the `BasicMCPClient` with your Vinkius MCP endpoint, wrap it in a `McpToolSpec`, and pass the tools to your `FunctionAgent`.

Yes, the agent can write the output of `calculate_routing_line` directly into your vector store. This lets you run semantic searches over previously calculated routes to save processing time.

The `search_autocomplete` tool allows your agent to clean up user input before indexing the location. It resolves messy, partial address strings into clean coordinates. This ensures your vector index stays highly accurate.

Use `search_country_filter` to force the agent to search only within designated borders. This prevents your index from getting polluted with global address matches that don't apply to your business.

This server processes only the specific latitude/longitude pairs and address strings you send. Vinkius processes these calls inside secure, temporary V8 isolates that do not write data to persistent disks. Your proprietary spatial indices remain entirely within your local vector database.

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