HelpCrunch MCP Server for LlamaIndex 11 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add HelpCrunch 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 HelpCrunch. "
"You have 11 tools available."
),
)
response = await agent.run(
"What tools are available in HelpCrunch?"
)
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 HelpCrunch MCP Server
Connect your HelpCrunch account to any AI agent and take full control of your customer communication and support workflows through natural conversation.
LlamaIndex agents combine HelpCrunch tool responses with indexed documents for comprehensive, grounded answers. Connect 11 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
- Chat Oversight — List all active and past conversations, retrieve full transcripts, and monitor response times.
- Customer Management — Access detailed customer profiles, add descriptive tags, and track user interaction history.
- Team Coordination — Reassign chats to specific team members or departments to ensure the right person handles every query.
- Proactive Support — Search through chats using complex filters to identify trends or urgent customer issues.
- Workflow Automation — Update chat statuses (closed, open, snoozed) directly from the chat interface.
- Operational Efficiency — List support departments and monitor the overall health of your customer service operations.
The HelpCrunch MCP Server exposes 11 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 HelpCrunch to LlamaIndex via MCP
Follow these steps to integrate the HelpCrunch 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 11 tools from HelpCrunch
Why Use LlamaIndex with the HelpCrunch MCP Server
LlamaIndex provides unique advantages when paired with HelpCrunch through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine HelpCrunch tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain HelpCrunch tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query HelpCrunch, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what HelpCrunch tools were called, what data was returned, and how it influenced the final answer
HelpCrunch + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the HelpCrunch MCP Server delivers measurable value.
Hybrid search: combine HelpCrunch real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query HelpCrunch 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 HelpCrunch for fresh data
Analytical workflows: chain HelpCrunch queries with LlamaIndex's data connectors to build multi-source analytical reports
HelpCrunch MCP Tools for LlamaIndex (11)
These 11 tools become available when you connect HelpCrunch to LlamaIndex via MCP:
add_customer_tag
Add a label/tag to a customer profile
get_chat_details
Get detailed information about a specific chat
get_customer_details
Get detailed profile information for a specific customer
list_chat_messages
Useful for understanding context or historical interactions. List all messages within a specific chat
list_chats
Each chat includes basic metadata and status. List all conversations (chats) in HelpCrunch
list_customers
List all customers (contacts) in HelpCrunch
list_departments
List all support departments
search_chats
Pass filter criteria as a JSON string in "filter_json" (e.g., {"status": "open"}). Search for chats using filters
send_message
Pass the payload as a JSON string in "body_json" (e.g., {"chat": 123, "text": "Hello"}). Send a message to a chat
update_chat_assignee
Assign a chat to a specific team member
update_chat_status
Update the status of a chat (e.g., closed, open)
Example Prompts for HelpCrunch in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with HelpCrunch immediately.
"List all open chats and show the last message for each."
"Search for all chats from the customer with email 'john.doe@example.com'."
"Tag customer ID 5592 with 'VIP' and 'Priority Support'."
Troubleshooting HelpCrunch MCP Server with LlamaIndex
Common issues when connecting HelpCrunch to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpHelpCrunch + LlamaIndex FAQ
Common questions about integrating HelpCrunch 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 HelpCrunch with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
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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 HelpCrunch to LlamaIndex
Get your token, paste the configuration, and start using 11 tools in under 2 minutes. No API key management needed.