Grid MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Check Api Health, Create New Operational Record, Get Authenticated User Profile, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Grid 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 Grid app connector for LlamaIndex is a standout in the Erp Operations category — giving your AI agent 12 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 Grid. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Grid?"
)
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 Grid MCP Server
Connect your WorkOnGrid account to any AI agent and take full control of your field operations and operational data management through natural conversation.
LlamaIndex agents combine Grid tool responses with indexed documents for comprehensive, grounded answers. Connect 12 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
- Worksheet Orchestration — List all operational worksheets and retrieve detailed technical metadata and structures programmatically
- Field Data Capture — Create, update, and search for records within your worksheets to track inspections, asset status, and team productivity
- Operational Visibility — Monitor analytical dashboards and manage team member access to maintain high-fidelity oversight of your workflows
- Asset Tracking — List and manage supported asset types to ensure precise inventory management and field record accuracy
- System Monitoring — Check API health and manage outbound webhooks directly through your agent for reliable operational automation
The Grid MCP Server exposes 12 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 12 Grid tools available for LlamaIndex
When LlamaIndex connects to Grid through Vinkius, your AI agent gets direct access to every tool listed below — spanning field-operations, data-digitization, worksheet-management, 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.
Verify Grid API connectivity
g., a new inspection report) into a specific worksheet. Add a new record to a worksheet
Get authenticated user info
Get details for a specific worksheet
List active webhooks
List available dashboards
List all operational worksheets
List common asset categories
List organization users
List records from a worksheet
Delete a record from a worksheet
Modify an existing operational record
Connect Grid to LlamaIndex via MCP
Follow these steps to wire Grid 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 Grid MCP Server
LlamaIndex provides unique advantages when paired with Grid through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Grid tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Grid tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Grid, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Grid tools were called, what data was returned, and how it influenced the final answer
Grid + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Grid MCP Server delivers measurable value.
Hybrid search: combine Grid real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Grid 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 Grid for fresh data
Analytical workflows: chain Grid queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Grid in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Grid immediately.
"List all active worksheets in my Grid account."
"Add a maintenance record to 'ws_456' for 'Excavator EX01'."
"Show me the latest dashboard status for field operations."
Troubleshooting Grid MCP Server with LlamaIndex
Common issues when connecting Grid to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpGrid + LlamaIndex FAQ
Common questions about integrating Grid MCP Server with LlamaIndex.