How to Use the AMcards MCP in LlamaIndex
Index your physical mailing history into LlamaIndex to ground your agent's outreach in actual data.
Works with every AI agent you already use
…and any MCP-compatible client
Connect AMcards MCP to LlamaIndex
Create your Vinkius account to connect AMcards 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.
Index your AMcards mailing history in LlamaIndex
Stop guessing what you sent to your clients. This MCP Server lets your LlamaIndex pipeline fetch your entire card log with `get_card_sending_history` and store it directly in your vector database. When your agent drafts a new message, it queries this index first. This ensures your custom physical cards never repeat the same message or use the wrong tone.
Match LlamaIndex queries to active AMcards campaigns
Keep your automated and manual touchpoints aligned. Your agent can check active outreach sequences using `list_drip_campaigns` and search against them to see if a customer is already queued for a card. If they aren't in a sequence, your agent executes `trigger_drip_campaign` to enroll them. This keeps your physical mailings highly relevant and prevents spamming your contacts with redundant mail.
Dynamic template selection inside LlamaIndex RAG loops
Let your data dictate the design of your physical mail. Your agent pulls your available layouts with `list_card_templates` and compares them against your indexed customer profile data to find the best match. Once the perfect design is identified, the agent uses `send_greeting_card` to dispatch the physical mail. This turns static customer data into highly targeted, physical touchpoints.
Set up AMcards 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 AMcards 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 AMcards tools.",
)
response = await agent.run("List recent AMcards data") Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by AMcards. 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 AMcards MCP in LlamaIndex
Use it with your favorite AI tools
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