How to Use the HeyReach MCP in LlamaIndex

Q: Can LlamaIndex draft personalized messages using HeyReach lead profiles?

Yes, by combining your vector index with the getleaddetails tool. The agent retrieves the lead's background, matches it with your product documentation, and prepares a message for sendlinkedinmessage.

Q: How do I filter which campaigns LlamaIndex can access?

You can use the allowedtools filter in the LlamaIndex MCP client to restrict access. This lets you expose safe tools like listcampaigns while keeping write tools like pausecampaign restricted to admin agents.

Index your LinkedIn conversations and campaign data directly into LlamaIndex vector stores using this MCP Server.

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Connect HeyReach MCP to LlamaIndex

Create your Vinkius account to connect HeyReach 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.

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Setup HeyReach with LlamaIndex

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Semantic Search Over LinkedIn Inbox

By using this MCP Server, LlamaIndex indexes your raw outreach data directly into vector stores for semantic search. By calling `list_conversations`, the LlamaIndex framework indexes your chat history, letting your agent search past interactions to draft highly personalized replies. This stops your LlamaIndex agent from hallucinating details during RAG workflows. It's pulling live facts directly from `get_lead_details` and matches them with your existing vector index to ground every message in actual prospect history.

Grounded Campaign Analytics with MCP Server

Connect the HeyReach MCP Server to your LlamaIndex RAG pipeline to query campaign performance using natural language. The LlamaIndex agent calls `list_campaigns` to pull active structures and indexes the metadata so you can ask which campaigns are currently active. You don't need to read raw JSON; you get plain-English summaries of your LlamaIndex outreach status. The framework combines these live API outputs with your internal sales playbooks to suggest the next best action.

Context-Rich Lead Enrichment

This MCP Server helps LlamaIndex build deep profiles of your prospects before launching outreach. The LlamaIndex agent runs `get_lead_details` with a LinkedIn URL, indexes the parsed profile data, and checks `list_lead_campaigns` to see where they are currently enrolled. This structured context is saved directly to your local LlamaIndex vector store. When it is time to write a message, `send_linkedin_message` uses this indexed history to make sure your pitch is hyper-targeted.

Setup guide

Set up HeyReach MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
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 provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to 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 HeyReach MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

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 HeyReach tools.",
)
response = await agent.run("List recent HeyReach data")

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Common questions about HeyReach MCP in LlamaIndex

Use the LlamaIndex MCP tool spec to connect to the server. The framework will call `list_campaigns` and load the resulting campaign configurations directly into your vector store for semantic querying.

Yes, by combining your vector index with the `get_lead_details` tool. The agent retrieves the lead's background, matches it with your product documentation, and prepares a message for `send_linkedin_message`.

Yes, the tool spec supports asynchronous execution for all endpoints. This allows your LlamaIndex agent to run `list_conversations` across multiple accounts simultaneously without blocking your pipeline.

You can use the allowed_tools filter in the LlamaIndex MCP client to restrict access. This lets you expose safe tools like `list_campaigns` while keeping write tools like `pause_campaign` restricted to admin agents.

Your LinkedIn session data and API profile information are processed strictly in memory during tool execution. Vinkius does not log or persist the payloads returned by `get_api_profile` or any inbox messages.

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