How to Use the Collect MCP in LlamaIndex

Q: Does LlamaIndex allow me to audit Collect campaigns?

Yes, by calling listcampaigns and embedding the results, you can ask your agent to compare current project progress against historical data.

Q: Can I link Collect messages to my LlamaIndex knowledge base?

You use listmessages to pull communication logs into your index. This makes your past correspondence searchable alongside your project files.

Q: How do I ensure LlamaIndex only accesses specific Collect tools?

You pass an allowedtools filter when defining your McpToolSpec. This restricts the agent's ability to only the functions you specify.

Index your Collect data into LlamaIndex for semantic search and grounded answers.

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Connect Collect MCP to LlamaIndex

Create your Vinkius account to connect Collect 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 Collect with LlamaIndex

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Indexing Collect data for LlamaIndex

Convert `get_campaign` and `list_requests` outputs into vector embeddings for your knowledge base. LlamaIndex stores this data so your agent answers questions based on real-time project status. This stops your agent from guessing. It builds a searchable history of every data collection effort.

Querying your MCP Server from LlamaIndex

Use `get_element_details` to pull specific field information into your index. Your RAG application now includes granular data points that were previously trapped in external systems. This provides context to your queries. Your index grows smarter with every request you perform.

Retrieving campaign insights in LlamaIndex

Run `list_campaigns` to populate your document store with current project metadata. LlamaIndex then allows you to query across your entire history of collections. This surfaces hidden bottlenecks. You gain a birds-eye view of your data acquisition health.

Setup guide

Set up Collect 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 Collect 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 Collect tools.",
)
response = await agent.run("List recent Collect data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Collect. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Collect MCP in LlamaIndex

You use the McpToolSpec to fetch data and index it into your vector store. Once indexed, you query your data using natural language.

Yes, by calling `list_campaigns` and embedding the results, you can ask your agent to compare current project progress against historical data.

You use `list_messages` to pull communication logs into your index. This makes your past correspondence searchable alongside your project files.

You pass an allowed_tools filter when defining your McpToolSpec. This restricts the agent's ability to only the functions you specify.

All Collect data is encrypted in transit and handled via ephemeral sessions. Your index only stores the specific text results returned by the tools.

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