Daftra 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 Daftra 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 Daftra. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Daftra?"
)
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 Daftra MCP Server
Integrate Daftra, the comprehensive cloud-based ERP and accounting software, directly into your AI workflow. Manage your clients, monitor invoices and estimates, and track business expenses using natural language.
LlamaIndex agents combine Daftra tool responses with indexed documents for comprehensive, grounded answers. Connect 10 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
- Client Management — List, search, and retrieve full profiles and interaction history for your clients.
- Billing Oversight — Monitor sales invoices and price estimates to stay on top of your revenue.
- Expense Tracking — Track and retrieve recorded business expenses across your organization.
- Inventory & Services — List products and services in your inventory directly via chat.
The Daftra 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 Daftra to LlamaIndex via MCP
Follow these steps to integrate the Daftra 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 Daftra
Why Use LlamaIndex with the Daftra MCP Server
LlamaIndex provides unique advantages when paired with Daftra through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Daftra tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Daftra tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Daftra, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Daftra tools were called, what data was returned, and how it influenced the final answer
Daftra + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Daftra MCP Server delivers measurable value.
Hybrid search: combine Daftra real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Daftra 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 Daftra for fresh data
Analytical workflows: chain Daftra queries with LlamaIndex's data connectors to build multi-source analytical reports
Daftra MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Daftra to LlamaIndex via MCP:
create_client
Resolves the newly generated client ID. Mutates the client and contact database state. Add a new client to the ERP database
get_client_details
Resolves detailed contact info and outstanding balances. Touches the granular CRM boundary. Get full profile and history for a specific client
get_invoice_details
Resolves line items, tax details, and payment history. Interacts with the detailed billing boundary. Get full details for a specific sales invoice
get_site_metadata
Resolves site identifiers and organizational settings. Interacts with the system configuration boundary. Retrieve general settings and metadata for your Daftra site
list_clients
Resolves client IDs, business names, and contact emails. Interacts with the client management boundary. List all clients in your Daftra account
list_estimates
Resolves estimate IDs, dates, and amounts. Interacts with the sales pipeline and quoting boundary. List all price estimates and quotes
list_expenses
Resolves expense IDs, categories, and amounts. Touches the accounting and expense tracking boundary. List all recorded business expenses
list_inventory_products
Resolves product IDs, names, and pricing. Interacts with the inventory management boundary. List all products and services in the inventory
list_invoices
Resolves invoice IDs, numbers, totals, and payment statuses. Touches the financial and sales boundary. List all sales invoices
search_clients_by_name
Resolves matching client profiles. Touches the search and discovery boundary. Search for a client by name keyword
Example Prompts for Daftra in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Daftra immediately.
"List all unpaid invoices from this month."
"Search for client 'John Smith' and show his contact details."
"List all business expenses recorded in the last 7 days."
Troubleshooting Daftra MCP Server with LlamaIndex
Common issues when connecting Daftra to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpDaftra + LlamaIndex FAQ
Common questions about integrating Daftra 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 Daftra 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 Daftra to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.