Collect MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Collect 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 MCP SERVER
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 Collect. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Collect?"
)
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 Collect MCP Server
Connect your AI to Collect, the secure platform for gathering information and documents from clients.
LlamaIndex agents combine Collect tool responses with indexed documents for comprehensive, grounded answers. Connect 10 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 active data collection campaigns and check their completion status.
- Request Sending — Send new data requests to clients by email for KYC, onboarding, or compliance workflows.
- Status Tracking — Check the status of individual requests, view messages, and monitor completion.
The Collect MCP Server exposes 10 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 Collect to LlamaIndex via MCP
Follow these steps to integrate the Collect 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 10 tools from Collect
Why Use LlamaIndex with the Collect MCP Server
LlamaIndex provides unique advantages when paired with Collect through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Collect tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Collect tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Collect, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Collect tools were called, what data was returned, and how it influenced the final answer
Collect + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Collect MCP Server delivers measurable value.
Hybrid search: combine Collect real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Collect 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 Collect for fresh data
Analytical workflows: chain Collect queries with LlamaIndex's data connectors to build multi-source analytical reports
Collect MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Collect to LlamaIndex via MCP:
create_request
Send a new data collection request to a recipient
get_campaign
Retrieve detailed information about a specific campaign
get_element_details
Retrieve details of a specific element (field/block) in a request
get_request
Retrieve details of a specific data request
get_team_info
Retrieve information about your team in Collect
get_user_info
Retrieve information about the currently authenticated user
list_campaigns
Retrieve a list of all data collection campaigns in Collect
list_messages
Retrieve a list of messages sent through Collect
list_requests
Retrieve all data requests for a specific campaign
send_message
Send a message to a recipient regarding a specific request
Example Prompts for Collect in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Collect immediately.
"Show me all active data collection campaigns."
"Send a data request to 'John Doe' (john@example.com) for the 'KYC Process' campaign."
"Send an automatic reminder to all clients with missing documents in the 'Tax 2025' campaign."
Troubleshooting Collect MCP Server with LlamaIndex
Common issues when connecting Collect to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpCollect + LlamaIndex FAQ
Common questions about integrating Collect 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 Collect 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 Collect to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.