How to Use the Moxie MCP in LlamaIndex

Q: Can LlamaIndex update Moxie records based on user queries?

Yes, the FunctionAgent can execute write operations like createtimeentry or createclient based on search results. It translates natural language requests into direct API actions.

Q: Can I filter which tools LlamaIndex has access to?

You can define an allowedtools list when initializing the MCP tool specification. This lets you restrict the agent to read-only tools like searchinvoices if you want to block creation tools.

Ground your LlamaIndex RAG applications in live project data and client portals using this MCP Server.

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Connect Moxie MCP to LlamaIndex

Create your Vinkius account to connect Moxie to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Moxie with LlamaIndex

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Index active projects for LlamaIndex RAG

The `search_projects` tool feeds live agency data directly into your LlamaIndex vector store using the MCP standard. Instead of guessing project health, your agent indexes active timelines to answer queries with zero hallucinations. By combining this with `create_task`, your RAG pipeline can identify bottlenecks and immediately assign work to resolve them. You get a search database that actually acts on its findings.

Turn invoice history into a searchable knowledge base

The `search_invoices` tool lets LlamaIndex query past financial records to answer complex billing questions. Your agent indexes the results, allowing you to ask which clients are late on payments. If a discrepancy is found, the agent can use `create_expense` to log missing costs or run `create_invoice` to correct the balance. This turns static billing data into an active, queryable index.

Build context-aware client portals with LlamaIndex

The `list_clients` tool helps LlamaIndex map user questions to their specific client portal profiles. When a customer submits a query, the system retrieves their contact details using `search_contacts` to ground the response. If the customer needs support, the agent automatically triggers `create_ticket` with the relevant conversation history attached. This ensures your support desk has full context before a human even steps in.

Setup guide

Set up Moxie MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Moxie MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Moxie tools.",
)
response = await agent.run("List recent Moxie data")

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Common questions about Moxie MCP in LlamaIndex

You use the McpToolSpec to load the 12 Moxie tools into your agent. LlamaIndex then queries tools like `search_projects` or `list_users` to build a vector index of your workspace.

Yes, the FunctionAgent can execute write operations like `create_time_entry` or `create_client` based on search results. It translates natural language requests into direct API actions.

The MCP Server runs on Vinkius infrastructure, which manages API handshake and token limits. LlamaIndex safely paginates through `list_clients` without crashing your pipeline.

You can define an allowed_tools list when initializing the MCP tool specification. This lets you restrict the agent to read-only tools like `search_invoices` if you want to block creation tools.

Your client details and contact info remain strictly inside your secure Moxie account. Vinkius processes all tool calls through ephemeral sandboxes that destroy data immediately after the query finishes.

Use it with your favorite AI tools

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