SafeGraph 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 SafeGraph as an MCP tool provider through the 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 SafeGraph. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in SafeGraph?"
)
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 SafeGraph MCP Server
Empower your AI with direct connectivity to SafeGraph, the foundational geospatial and mobility dataset trusted by top analytics and enterprise organizations globally. This robust integration converts your AI into an expert geographical analyst capable of retrieving precise intelligence surrounding global structures, Points of Interest (POIs), and detailed patterns—all without touching complex database pipelines.
LlamaIndex agents combine SafeGraph tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through the 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
- Rich Context on POIs — Fetch exhaustive lists of businesses or brands within targeted radii (
search_distance_radius,search_brand_places). You can also slice the results according to their designated NAICS industry codes region-to-region (search_industry_naics). - Deep Geospatial Footprints — Look up exact WKT polygons for targeted individual buildings (
lookup_building_geometry) or identify everything bounded inside designated custom city borders (search_wkt_polygon). Understand structural hierarchies immediately by querying parent containers like malls or industrial complexes (lookup_parent_polygon). - Pedestrian and Mobility Insights — Audit recent visit metrics, dwell times, and absolute foot traffic measurements attached to individual structures leveraging historical aggregation points (
lookup_place_patterns). - Native GraphQL Exploration — Pass perfectly structured GraphQL queries straight to the root mapping infrastructure for fully-unlocked edge cases (
graphql_raw_query). Request and resolve bulk Placekeys efficiently on demand (batch_lookup_placekeys).
The SafeGraph 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 SafeGraph to LlamaIndex via MCP
Follow these steps to integrate the SafeGraph 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 SafeGraph
Why Use LlamaIndex with the SafeGraph MCP Server
LlamaIndex provides unique advantages when paired with SafeGraph through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine SafeGraph tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain SafeGraph tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query SafeGraph, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what SafeGraph tools were called, what data was returned, and how it influenced the final answer
SafeGraph + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the SafeGraph MCP Server delivers measurable value.
Hybrid search: combine SafeGraph real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query SafeGraph 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 SafeGraph for fresh data
Analytical workflows: chain SafeGraph queries with LlamaIndex's data connectors to build multi-source analytical reports
SafeGraph MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect SafeGraph to LlamaIndex via MCP:
batch_lookup_placekeys
Provide them as a JSON array. Performs multiple Placekey lookups in a single request
graphql_raw_query
Provide the query string and optional variables. Executes a raw GraphQL query against the SafeGraph API
lookup_building_geometry
Retrieves the building footprint (polygon) for a specific Placekey
lookup_parent_polygon
Identifies the parent Placekey for a location (e.g., mall or airport)
lookup_place_patterns
Retrieves historical foot traffic patterns for a specific Placekey
lookup_placekey
Retrieves detailed attributes for a specific location by its Placekey
search_brand_places
g., "Starbucks") in a specific city. Searches for locations of a specific brand in a city
search_distance_radius
Specify lat, lon, and radius in meters. Searches for places within a specific radius from a point
search_industry_naics
Searches for places by NAICS industry code and region
search_wkt_polygon
Finds all places within a specific geometric polygon (WKT)
Example Prompts for SafeGraph in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with SafeGraph immediately.
"Search for all the Starbucks branches strictly inside the city of Seattle, WA."
"Check what the detailed building geometry polygon is for Placekey '22m-xyz-1234'."
"Can you gather the historical pedestrian traffic patterns evaluating typical visit frequencies around Placekey '123-abc-987'?"
Troubleshooting SafeGraph MCP Server with LlamaIndex
Common issues when connecting SafeGraph to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpSafeGraph + LlamaIndex FAQ
Common questions about integrating SafeGraph 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 SafeGraph 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 SafeGraph to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.