Clustdoc 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 Clustdoc 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 Clustdoc. "
"You have 8 tools available."
),
)
response = await agent.run(
"What tools are available in Clustdoc?"
)
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 Clustdoc MCP Server
Connect your Clustdoc account to any AI agent and take full control of your client onboarding and document collection through natural conversation. Streamline how you manage complex applications and workflows natively.
LlamaIndex agents combine Clustdoc 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
- Template Oversight — List and retrieve details for all onboarding workflow templates configured in your account natively
- Dossier Intelligence — Access and monitor individual client applications (dossiers) and their current progress flawlessly
- Application Lifecycle — Launch new onboarding sessions for clients using pre-defined templates securely
- Invitation Logistics — Trigger automated portal invitation emails to clients directly from your chat interface flawlessly
- Team Management — List all teams and members within your Clustdoc account to manage access flawlessly
- integrated Visibility — Retrieve detailed application metadata including status and contact information directly within your workspace
The Clustdoc 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 Clustdoc to LlamaIndex via MCP
Follow these steps to integrate the Clustdoc 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 Clustdoc
Why Use LlamaIndex with the Clustdoc MCP Server
LlamaIndex provides unique advantages when paired with Clustdoc through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Clustdoc tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Clustdoc tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Clustdoc, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Clustdoc tools were called, what data was returned, and how it influenced the final answer
Clustdoc + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Clustdoc MCP Server delivers measurable value.
Hybrid search: combine Clustdoc real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Clustdoc 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 Clustdoc for fresh data
Analytical workflows: chain Clustdoc queries with LlamaIndex's data connectors to build multi-source analytical reports
Clustdoc MCP Tools for LlamaIndex (8)
These 8 tools become available when you connect Clustdoc to LlamaIndex via MCP:
get_application_status_details
Get detailed status and progress for a specific client dossier
get_my_clustdoc_profile
Retrieve information about the authenticated user
get_workflow_configuration
Get detailed configuration for a specific onboarding template
launch_new_onboarding
Launch a new onboarding application for a client
list_client_dossiers
List all active and completed client applications (dossiers)
list_clustdoc_teams
List all teams and members in the Clustdoc account
list_onboarding_templates
List all onboarding workflow templates
send_onboarding_invitation
Send the portal invitation email to the client for a specific dossier
Example Prompts for Clustdoc in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Clustdoc immediately.
"List all active client dossiers in Clustdoc."
"Launch a new 'Standard Business Onboarding' for john@example.com."
"What is the status of the dossier for 'TechFlow Inc'?"
Troubleshooting Clustdoc MCP Server with LlamaIndex
Common issues when connecting Clustdoc to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpClustdoc + LlamaIndex FAQ
Common questions about integrating Clustdoc 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 Clustdoc 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 Clustdoc to LlamaIndex
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.