Mailshake MCP Server for LlamaIndex 9 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Mailshake as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Mailshake. "
"You have 9 tools available."
),
)
response = await agent.run(
"What tools are available in Mailshake?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Mailshake MCP Server
Connect your Mailshake account to any AI agent to automate your cold outreach and sales engagement workflows. This MCP server enables your agent to manage campaigns, promote prospects to lead status, and track email interactions directly from natural language interfaces.
LlamaIndex agents combine Mailshake tool responses with indexed documents for comprehensive, grounded answers. Connect 9 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Campaign Management — List all outreach campaigns, retrieve detailed sequences, and pause or unpause sending
- Lead Tracking — Monitor qualified leads, retrieve interaction histories, and update prospect statuses
- Prospect Ingestion — Programmatically add new recipients to existing campaigns to keep your pipeline full
- Message Insights — List sent and received messages and retrieve full content for automated sentiment analysis or follow-up planning
- Audience Oversight — List all recipients in a campaign and monitor their individual engagement stages (Sent, Opened, Replied)
The Mailshake MCP Server exposes 9 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Mailshake to LlamaIndex via MCP
Follow these steps to integrate the Mailshake MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 9 tools from Mailshake
Why Use LlamaIndex with the Mailshake MCP Server
LlamaIndex provides unique advantages when paired with Mailshake through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Mailshake tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Mailshake tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Mailshake, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Mailshake tools were called, what data was returned, and how it influenced the final answer
Mailshake + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Mailshake MCP Server delivers measurable value.
Hybrid search: combine Mailshake real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Mailshake to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Mailshake for fresh data
Analytical workflows: chain Mailshake queries with LlamaIndex's data connectors to build multi-source analytical reports
Mailshake MCP Tools for LlamaIndex (9)
These 9 tools become available when you connect Mailshake to LlamaIndex via MCP:
add_prospects_to_campaign
Requires a JSON body with recipient details. Add new prospects to an existing campaign
get_campaign_details
Get details for a specific campaign
get_lead_history
Get history for a specific lead
get_message_content
Get content for a specific email message
list_campaign_leads
List qualified leads
list_campaign_recipients
List all recipients in a campaign
list_outreach_campaigns
List all outreach campaigns
list_outreach_messages
List sent and received messages
pause_outreach_campaign
Pause a running campaign
Example Prompts for Mailshake in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Mailshake immediately.
"List all my active outreach campaigns in Mailshake."
"Show recent leads for the 'Partnership' campaign."
"Pause the campaign with ID '12345'."
Troubleshooting Mailshake MCP Server with LlamaIndex
Common issues when connecting Mailshake to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpMailshake + LlamaIndex FAQ
Common questions about integrating Mailshake MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Mailshake with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Mailshake to LlamaIndex
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.