Moxie MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Create Client, Create Expense, Create Invoice, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Moxie 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 Moxie app connector for LlamaIndex is a standout in the Productivity 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 Moxie. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Moxie?"
)
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 Moxie MCP Server
Connect your Moxie workspace to any AI agent and manage your freelance or agency business through natural conversation.
LlamaIndex agents combine Moxie 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
- Clients & Contacts — List clients, create new ones, search contacts
- Projects & Tasks — Search/create projects, create tasks
- Invoices — Search payable invoices, create new ones
- Time & Expenses — Log time entries, record expenses
- Tickets — Create support tickets
- Users — List workspace team members
The Moxie 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 Moxie tools available for LlamaIndex
When LlamaIndex connects to Moxie through Vinkius, your AI agent gets direct access to every tool listed below — spanning freelance-management, invoicing, time-tracking, 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.
Create a new client
Log an expense
Create a new invoice
Create a new project
Create a new task
Create a support ticket
Log time
List all clients in Moxie
List workspace users
Search for contacts
Search for payable invoices
Search for projects
Connect Moxie to LlamaIndex via MCP
Follow these steps to wire Moxie 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 Moxie MCP Server
LlamaIndex provides unique advantages when paired with Moxie through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Moxie tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Moxie tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Moxie, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Moxie tools were called, what data was returned, and how it influenced the final answer
Moxie + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Moxie MCP Server delivers measurable value.
Hybrid search: combine Moxie real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Moxie 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 Moxie for fresh data
Analytical workflows: chain Moxie queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Moxie in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Moxie immediately.
"List all clients and their projects."
"Log 2 hours of consulting on the Acme Corp project."
"Create an invoice for Beta Design."
Troubleshooting Moxie MCP Server with LlamaIndex
Common issues when connecting Moxie to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpMoxie + LlamaIndex FAQ
Common questions about integrating Moxie MCP Server with LlamaIndex.