Enrich CRM MCP Server for LlamaIndexGive LlamaIndex instant access to 5 tools to Enrich Company, Enrich Person, Find Email, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Enrich CRM 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 App Connector for LlamaIndex
The Enrich CRM app connector for LlamaIndex is a standout in the Productivity category — giving your AI agent 5 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 Enrich CRM. "
"You have 5 tools available."
),
)
response = await agent.run(
"What tools are available in Enrich CRM?"
)
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 Enrich CRM MCP Server
Connect your Enrich CRM account to any AI agent to streamline your B2B intelligence and sales automation workflows through natural conversation.
LlamaIndex agents combine Enrich CRM tool responses with indexed documents for comprehensive, grounded answers. Connect 5 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
- Company Orchestration — Retrieve detailed firmographics, technical stacks, and financial data using only a company domain programmatically
- Person Enrichment — Access professional backgrounds, verified emails, and direct phone lines for your target prospects to maintain a high-fidelity database
- Email Discovery — Programmatically find and verify professional email addresses using name and domain combinations directly through your agent
- Phone Intelligence — Retrieve direct phone lines to bypass switchboards and reach decision-makers faster
- Account Visibility — Monitor your remaining credits and subscription status directly through your agent for instant operational reporting
The Enrich CRM MCP Server exposes 5 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.
All 5 Enrich CRM tools available for LlamaIndex
When LlamaIndex connects to Enrich CRM through Vinkius, your AI agent gets direct access to every tool listed below — spanning enrich-crm, lead-enrichment, b2b-data, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Enrich company data
Enrich person data
Find a professional email address
Find a professional phone number
Check account status
Connect Enrich CRM to LlamaIndex via MCP
Follow these steps to wire Enrich CRM into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Enrich CRM MCP Server
LlamaIndex provides unique advantages when paired with Enrich CRM through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Enrich CRM tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Enrich CRM tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Enrich CRM, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Enrich CRM tools were called, what data was returned, and how it influenced the final answer
Enrich CRM + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Enrich CRM MCP Server delivers measurable value.
Hybrid search: combine Enrich CRM real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Enrich CRM 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 Enrich CRM for fresh data
Analytical workflows: chain Enrich CRM queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Enrich CRM in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Enrich CRM immediately.
"Enrich the company with domain 'google.com' using Enrich CRM."
"Find the professional email for 'Satya Nadella' at 'microsoft.com'."
"Check my remaining enrichment credits."
Troubleshooting Enrich CRM MCP Server with LlamaIndex
Common issues when connecting Enrich CRM to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpEnrich CRM + LlamaIndex FAQ
Common questions about integrating Enrich CRM MCP Server with LlamaIndex.