Mapflow MCP Server for LlamaIndexGive LlamaIndex instant access to 7 tools to Create Processing, Create Project, Get Processing Result, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Mapflow 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 App Connector for LlamaIndex
The Mapflow app connector for LlamaIndex is a standout in the Artificial Intelligence category — giving your AI agent 7 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 Mapflow. "
"You have 7 tools available."
),
)
response = await agent.run(
"What tools are available in Mapflow?"
)
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 Mapflow MCP Server
Connect your Mapflow account to any AI agent and manage geospatial AI processing through natural conversation.
LlamaIndex agents combine Mapflow tool responses with indexed documents for comprehensive, grounded answers. Connect 7 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
- Project Management — Create and manage mapping projects
- Image Processing — Trigger AI models on satellite and drone imagery
- Task Tracking — Monitor processing status and completion
- Dataset Browsing — Access generated vector datasets and polygons
- Model Management — Browse available AI models (buildings, roads, forests)
The Mapflow MCP Server exposes 7 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.
All 7 Mapflow tools available for LlamaIndex
When LlamaIndex connects to Mapflow through Vinkius, your AI agent gets direct access to every tool listed below — spanning geospatial-ai, satellite-imagery, drone-mapping, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Pass data as a JSON string. Start a new imagery analysis
Pass data as a JSON string. Create a new project
Get processing result data
Check status of a processing job
List available geospatial AI models
List all geospatial processings
List all MapFlow projects
Connect Mapflow to LlamaIndex via MCP
Follow these steps to wire Mapflow into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Mapflow MCP Server
LlamaIndex provides unique advantages when paired with Mapflow through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Mapflow tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Mapflow tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Mapflow, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Mapflow tools were called, what data was returned, and how it influenced the final answer
Mapflow + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Mapflow MCP Server delivers measurable value.
Hybrid search: combine Mapflow real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Mapflow 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 Mapflow for fresh data
Analytical workflows: chain Mapflow queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Mapflow in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Mapflow immediately.
"List available AI models and my active projects."
"Start processing building footprints for the Seattle project."
"Check status of task tsk_8901 and show dataset results."
Troubleshooting Mapflow MCP Server with LlamaIndex
Common issues when connecting Mapflow to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpMapflow + LlamaIndex FAQ
Common questions about integrating Mapflow MCP Server with LlamaIndex.