How to Use the PHC GO MCP in LlamaIndex
Index your entire PHC GO database into LlamaIndex for semantic search and grounded document generation.
Works with every AI agent you already use
…and any MCP-compatible client
Connect PHC GO MCP to LlamaIndex
Create your Vinkius account to connect PHC GO to LlamaIndex — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.
Key Capabilities
Semantic indexing for PHC GO data
Convert your ERP output into a searchable knowledge base within LlamaIndex. By running `list_products` and indexing the results, your agent understands your catalog semantically rather than just by ID. This allows for natural language queries against your inventory. You move beyond simple lookups and start answering complex questions about product availability and specifications.
Grounded document creation in LlamaIndex
Avoid hallucinations by forcing your agent to query `get_product_details` and `list_taxes` before it generates any document. LlamaIndex keeps these API results in context for the final output. Your agent builds accurate invoices by pulling live data from the ERP. It references the index to ensure that every tax rate and product description matches your current system state.
Unified knowledge access for PHC GO
Combine your private documents with live ERP information using the MCP tool spec. You query the index to retrieve historical data while simultaneously calling `list_current_accounts` for real-time status. This creates a single source of truth for your agent. It balances static business knowledge with the dynamic, real-time data coming directly from your ERP environment.
Set up PHC GO MCP in LlamaIndex
Prerequisites
- Python 3.10+ installed
-
llama-index-tools-mcppackage - 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 providesBasicMCPClientandMcpToolSpec. - 2
Connect with BasicMCPClient
Point
BasicMCPClientto 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 PHC GO MCP tools into nativeFunctionToolobjects that any LlamaIndex agent can use. - 4
Run with any LLM
Create a
FunctionAgentwith the tools and your preferred LLM. SwapOpenAIforAnthropic,Gemini, or any LlamaIndex-supported provider.
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 PHC GO tools.",
)
response = await agent.run("List recent PHC GO data") Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by PHC GO. 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.
Why Choose Vinkius
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Built-in savings
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lower AI costs
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Common questions about PHC GO MCP in LlamaIndex
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