How to Use the ConnectWise MCP in LlamaIndex

Q: How do I configure LlamaIndex with ConnectWise?

Install the required integration using pip install llama-index-tools-mcp first. Then, initialize BasicMCPClient with your Vinkius URL and convert the tools using McpToolSpec.

Q: Can I search ConnectWise tickets using natural language in LlamaIndex?

Your agent handles this by calling searchticketsbysummary with keywords extracted from the user's query. It then indexes the matching tickets to formulate a precise response.

Index your ConnectWise support history into LlamaIndex for grounded, hallucination-free RAG.

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Connect ConnectWise MCP to LlamaIndex

Create your Vinkius account to connect ConnectWise 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 ConnectWise with LlamaIndex

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Build a searchable support index with LlamaIndex

The `list_service_tickets` tool pulls raw ticket history from your PSA directly into your query pipeline. LlamaIndex then indexes this text, turning past resolutions into a searchable knowledge base for your support team. This setup eliminates hallucinations by grounding your agent's responses in actual historical data. When a user asks about an old issue, the agent searches the vector store instead of guessing.

Map customer relationships automatically

Your agent runs `list_companies` to retrieve complete organizational profiles, including territories and statuses. It immediately pairs this with `get_company` to build a rich semantic profile of your clients. Storing these profiles in your index lets the agent instantly recall client contexts during live chats. You get immediate background information without manual lookups.

Track sales and service activities in real time

The `list_sales_activities` tool exposes current pipeline events and interactions directly to your index. Your agent monitors these activities to update status reports or trigger follow-up tasks. By feeding this data straight into a LlamaIndex `FunctionAgent`, you keep your internal reports updated. The agent handles the collection and structuring so you don't have to write custom cron jobs.

Setup guide

Set up ConnectWise 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 ConnectWise 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 ConnectWise tools.",
)
response = await agent.run("List recent ConnectWise data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by ConnectWise Manage. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about ConnectWise MCP in LlamaIndex

Install the required integration using `pip install llama-index-tools-mcp` first. Then, initialize `BasicMCPClient` with your Vinkius URL and convert the tools using `McpToolSpec`.

Yes, you can filter which capabilities your agent accesses. Use the `allowed_tools` list to restrict the agent to reading data with `get_ticket` while blocking creation tools.

This MCP Server provides clean, structured JSON payloads directly from your PSA. LlamaIndex parses these payloads into nodes, ensuring your vector search queries match real ticket summaries.

Your agent handles this by calling `search_tickets_by_summary` with keywords extracted from the user's query. It then indexes the matching tickets to formulate a precise response.

Yes, all client profiles, contacts, and ticket contents are processed through secure, ephemeral MCP isolates. Vinkius never caches your PSA credentials or stores the retrieved records.

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