Holded MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Create Invoice, List Contacts, List Credit Notes, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Holded 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 Holded 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 Holded. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Holded?"
)
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 Holded MCP Server
Connect your Holded account to any AI agent and take full control of your business operations and ERP workflows through natural conversation.
LlamaIndex agents combine Holded 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
- Sales Lifecycle — Manage everything from quotes and sales orders to invoices and credit notes programmatically
- Purchase Tracking — Monitor supplier relationships and manage purchase orders and invoices with ease
- CRM & Contacts — Organize your customer base, inventory products, and business expenses in one centralized hub
- Treasury & Payments — Monitor payments, treasury accounts, and financial health directly through your agent
- Inventory Control — List and manage products and stock levels to ensure your business never misses a beat
The Holded 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 Holded tools available for LlamaIndex
When LlamaIndex connects to Holded through Vinkius, your AI agent gets direct access to every tool listed below — spanning invoicing, accounting, inventory-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.
Requires contact ID and items. Create a new invoice
List CRM contacts
List all credit notes
List business expenses
List all sales invoices
List recent payments
List inventory products
List purchase invoices
List purchase orders
List all quotes
List all sales orders
List active webhooks
Connect Holded to LlamaIndex via MCP
Follow these steps to wire Holded 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 Holded MCP Server
LlamaIndex provides unique advantages when paired with Holded through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Holded tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Holded tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Holded, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Holded tools were called, what data was returned, and how it influenced the final answer
Holded + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Holded MCP Server delivers measurable value.
Hybrid search: combine Holded real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Holded 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 Holded for fresh data
Analytical workflows: chain Holded queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Holded in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Holded immediately.
"List all my unpaid sales invoices from Holded."
"Create a new contact 'John Doe' as a lead with email 'john@example.com'."
"Show me the last 5 business expenses."
Troubleshooting Holded MCP Server with LlamaIndex
Common issues when connecting Holded to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpHolded + LlamaIndex FAQ
Common questions about integrating Holded MCP Server with LlamaIndex.