MOBIDI MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Check Mobidi Status, Create Record, Delete Record, and more

Name: MOBIDI
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

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LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add MOBIDI as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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The MOBIDI MCP Server 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.

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python

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 MOBIDI. "
            "You have 12 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in MOBIDI?"
    )
    print(response)

asyncio.run(main())

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* 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 MOBIDI MCP Server

Connect your MOBIDI platform to any AI agent and manage business intelligence data.

LlamaIndex agents combine MOBIDI 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

Data Queries — Run custom queries and count matching records
CRUD Operations — Create, read, update, and delete records of any entity type
Reports — List, inspect, and execute BI reports
Data Model — Explore available entity types
System Services — View available platform services

The MOBIDI MCP Server exposes 12 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 12 MOBIDI tools available for LlamaIndex

When LlamaIndex connects to MOBIDI through Vinkius, your AI agent gets direct access to every tool listed below — spanning crud-operations, data-querying, reporting-dashboards, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

check

Check mobidi status on MOBIDI

Verify API connectivity

create

Create record on MOBIDI

Create a record

delete

Delete record on MOBIDI

Delete a record

execute

Execute report on MOBIDI

Execute a report

get

Get record by id on MOBIDI

Get record by ID

get

Get record count on MOBIDI

Count records

get

Get report on MOBIDI

Get report details

get

Get services on MOBIDI

List system services

list

List entity types on MOBIDI

List entity types

list

List records on MOBIDI

Query records

list

List reports on MOBIDI

List reports

update

Update record on MOBIDI

Update a record

Connect MOBIDI to LlamaIndex via MCP

Follow these steps to wire MOBIDI into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

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 12 tools from MOBIDI

Why Use LlamaIndex with the MOBIDI MCP Server

LlamaIndex provides unique advantages when paired with MOBIDI through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine MOBIDI tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain MOBIDI tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query MOBIDI, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what MOBIDI tools were called, what data was returned, and how it influenced the final answer

MOBIDI + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the MOBIDI MCP Server delivers measurable value.

Hybrid search: combine MOBIDI real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query MOBIDI 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 MOBIDI for fresh data

Analytical workflows: chain MOBIDI queries with LlamaIndex's data connectors to build multi-source analytical reports

Example Prompts for MOBIDI in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with MOBIDI immediately.

"Query all records where status is active."

"Execute the monthly sales report."

"List all entity types in the data model."

Troubleshooting MOBIDI MCP Server with LlamaIndex

Common issues when connecting MOBIDI to LlamaIndex through Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

MOBIDI + LlamaIndex FAQ

Common questions about integrating MOBIDI MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query MOBIDI tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.

Does LlamaIndex support async MCP calls?

Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.

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