Holded MCP Server for LlamaIndex 11 tools — connect in under 2 minutes
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 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 Holded. "
"You have 11 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 ERP platform to any AI agent and take full control of your invoicing, CRM, and project management through natural conversation.
LlamaIndex agents combine Holded tool responses with indexed documents for comprehensive, grounded answers. Connect 11 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
- Invoicing Oversight — List all documents, retrieve detailed invoice data, and monitor payment statuses efficiently.
- CRM & Contact Management — Access lists of clients, suppliers, and leads, and retrieve full profile information for better relationship management.
- Project & Task Tracking — List active projects and monitor tasks across your entire portfolio to ensure deadlines are met.
- Inventory & Products — Access your product catalog and update stock levels directly from the chat interface.
- Business Intelligence — Retrieve account and organization metadata to maintain a high-level overview of your business operations.
- Unified ERP — Bridge the gap between your accounting and operations using the comprehensive Holded API.
The Holded MCP Server exposes 11 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 Holded to LlamaIndex via MCP
Follow these steps to integrate the Holded 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 11 tools from Holded
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
Holded MCP Tools for LlamaIndex (11)
These 11 tools become available when you connect Holded to LlamaIndex via MCP:
get_api_profile
Retrieve information about the authenticated account
get_contact_details
Get detailed profile information for a specific contact
get_invoice_details
Get detailed information about a specific invoice
get_product_details
Get detailed information for a specific product
get_project_details
Get detailed configuration and status for a project
list_all_tasks
List tasks across all projects
list_contacts
Useful for finding the contact ID required for documents. List all contacts (clients, suppliers, leads) in Holded
list_invoices
Use this to monitor billing and find IDs for specific document actions. List all invoices in your Holded account
list_products
List all products and services in your Holded inventory
list_projects
List all active and past projects
update_product_stock
Pass details as a JSON string in "body_json" (requires warehouseId and new quantity). Update the stock level for a specific product
Example Prompts for Holded in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Holded immediately.
"List all active projects and show the last task for each."
"Find contact 'Acme Corp' and show their recent invoices."
"Show me the details for product ID 'prod_992' and its stock level."
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.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Holded 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 Holded to LlamaIndex
Get your token, paste the configuration, and start using 11 tools in under 2 minutes. No API key management needed.