How to Use the Advice Slip MCP in LlamaIndex
Index Advice Slip data into your LlamaIndex knowledge base to ground your RAG applications in external wisdom.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Advice Slip MCP to LlamaIndex
Create your Vinkius account to connect Advice Slip 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.
Grounding LlamaIndex with advice
Run `get_random_advice` and pass the output directly to your vector store. LlamaIndex treats these strings as documents, making them available for future semantic searches. This builds a knowledge base that updates itself. Your agents stop hallucinating when they have actual API-provided text to reference.
Keyword indexing in LlamaIndex
Use `search_advice` to fetch batches of data for your index. Once retrieved, the tool output is ingested into your pipeline for immediate querying. Your RAG application gains a broader context. It doesn't just rely on static files anymore.
Managing Advice Slip IDs in LlamaIndex
Call `get_advice_by_id` to pull specific records into your searchable index. This is useful for building a curated library of advice that your agent can cite. You'll define exactly which pieces of data the agent uses. It keeps your index clean and relevant to the user's specific problem.
Set up Advice Slip 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 Advice Slip 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 Advice Slip tools.",
)
response = await agent.run("List recent Advice Slip data") Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Advice Slip. 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 Advice Slip MCP in LlamaIndex
Use it with your favorite AI tools
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