How to Use the ClickSend MCP in LlamaIndex
Index your ClickSend communication logs into LlamaIndex to build a searchable knowledge base of SMS and voice interactions.
Works with every AI agent you already use
…and any MCP-compatible client
Connect ClickSend MCP to LlamaIndex
Create your Vinkius account to connect ClickSend 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.
Build RAG pipelines over ClickSend MCP Server data
LlamaIndex treats APIs as live document sources, letting you pull records using `get_sms_outbound_history` and index them directly. You run the query, fetch the historical logs, and feed them into your vector store. The raw API data becomes a permanent part of your searchable knowledge base. Now your agent answers questions based on actual message logs rather than guessing. If someone asks what you texted a specific client last Tuesday, the RAG pipeline queries the index and returns the exact transcript.
Sync contact lists for semantic search
By running `list_clicksend_contacts`, you ingest your entire address book directly into LlamaIndex. Finding the right recipient happens much faster when your agent understands the context behind every contact record. The MCP tool fetches names and numbers in one pass. The agent can then cross-reference those names with other indexed documents. It finds the right phone number, formats it to E.164, and fires off a text using `send_clicksend_sms` without you lifting a finger.
Track multi-channel outreach
You can index data from `get_voice_call_history` and `get_physical_mail_history` to build a complete timeline of customer touchpoints. Marketing relies on knowing exactly what went out and when. LlamaIndex pulls these distinct channels into a unified graph. When a user queries the system about a specific campaign, the engine retrieves the exact delivery statuses. It gives you a grounded, hallucination-free summary of your physical and digital outreach.
Set up ClickSend 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 ClickSend 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 ClickSend tools.",
)
response = await agent.run("List recent ClickSend data") Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by ClickSend. 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 ClickSend MCP in LlamaIndex
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