Reply.io MCP Server for LlamaIndex 8 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Reply.io 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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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 Reply.io. "
"You have 8 tools available."
),
)
response = await agent.run(
"What tools are available in Reply.io?"
)
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 Reply.io MCP Server
Connect Reply.io to your AI agent and manage your multi-channel sales engagement platform conversationally.
LlamaIndex agents combine Reply.io tool responses with indexed documents for comprehensive, grounded answers. Connect 8 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, create, and pause outreach campaigns across email, LinkedIn, calls, and SMS channels.
- Prospect Tracking — Add prospects, check engagement statuses (opened, replied, bounced), and manage contact lists.
- Sequence Analytics — Pull performance metrics per campaign and per step — open rates, reply rates, and conversion data.
- People Search — Use Reply.io's contact database to find prospect emails and enrich your outreach lists.
The Reply.io MCP Server exposes 8 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 Reply.io to LlamaIndex via MCP
Follow these steps to integrate the Reply.io 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 8 tools from Reply.io
Why Use LlamaIndex with the Reply.io MCP Server
LlamaIndex provides unique advantages when paired with Reply.io through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Reply.io tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Reply.io tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Reply.io, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Reply.io tools were called, what data was returned, and how it influenced the final answer
Reply.io + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Reply.io MCP Server delivers measurable value.
Hybrid search: combine Reply.io real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Reply.io 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 Reply.io for fresh data
Analytical workflows: chain Reply.io queries with LlamaIndex's data connectors to build multi-source analytical reports
Reply.io MCP Tools for LlamaIndex (8)
These 8 tools become available when you connect Reply.io to LlamaIndex via MCP:
add_person
io. Add a person
get_campaign
Get campaign
get_campaign_stats
Get campaign stats
list_campaigns
io outreach campaigns. List campaigns
list_email_accounts
List email accounts
list_people
io. List people
pause_person
Pause a person
resume_person
Resume a person
Example Prompts for Reply.io in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Reply.io immediately.
"Show me the performance of my 'CTO Outreach' campaign."
"Add prospect alex@techstart.com to the 'Series B Founders' sequence."
"Which prospects replied positively this week?"
Troubleshooting Reply.io MCP Server with LlamaIndex
Common issues when connecting Reply.io to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpReply.io + LlamaIndex FAQ
Common questions about integrating Reply.io 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?
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Connect Reply.io to LlamaIndex
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.