Resend MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Resend as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
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 Resend. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Resend?"
)
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 Resend MCP Server
Connect your Resend account to any AI agent and take full control of your email infrastructure through natural conversation.
LlamaIndex agents combine Resend tool responses with indexed documents for comprehensive, grounded answers. Connect 10 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
- Send Emails — Dispatch transactional emails with HTML content, attachments, and reply-to headers instantly from your agent
- Track Delivery — Retrieve complete delivery metadata, bounce information, and open/click analytics for any sent email
- Domain Management — List verified sending domains, inspect DNS records (SPF/DKIM), and trigger verification checks
- Audience & Contact Management — Browse audiences, list subscribers, and add new contacts programmatically for broadcast campaigns
- Broadcast Campaigns — Monitor active broadcast campaigns, check delivery statuses, and audit mass email operations
- API Key Auditing — List active API keys and their permission scopes to maintain security hygiene
The Resend MCP Server exposes 10 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 Resend to LlamaIndex via MCP
Follow these steps to integrate the Resend 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 10 tools from Resend
Why Use LlamaIndex with the Resend MCP Server
LlamaIndex provides unique advantages when paired with Resend through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Resend tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Resend tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Resend, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Resend tools were called, what data was returned, and how it influenced the final answer
Resend + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Resend MCP Server delivers measurable value.
Hybrid search: combine Resend real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Resend 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 Resend for fresh data
Analytical workflows: chain Resend queries with LlamaIndex's data connectors to build multi-source analytical reports
Resend MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Resend to LlamaIndex via MCP:
add_domain
Returns DNS records to configure. Add a new sending domain
create_contact
Add a contact to an audience
get_domain
Get domain details
get_email
Get email delivery status
list_api_keys
List all API keys
list_audiences
List email audiences
list_contacts
List contacts in an audience
list_domains
List verified sending domains
send_batch_emails
Each email needs from, to, subject, and html fields. Send batch of emails
send_email
Returns email ID for tracking delivery status. Send a transactional email
Example Prompts for Resend in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Resend immediately.
"Send a welcome email to john@example.com from our onboarding address."
"Show me all our verified sending domains and their DNS status."
"List all contacts in our newsletter audience."
Troubleshooting Resend MCP Server with LlamaIndex
Common issues when connecting Resend to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpResend + LlamaIndex FAQ
Common questions about integrating Resend 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 Resend 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 Resend to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.