How to Use the Fusioo MCP in LlamaIndex

Q: Does LlamaIndex update records in Fusioo?

Yes. You can trigger updateapprecord through the agent once it has analyzed your indexed data. It allows for a loop of search, analyze, and modify.

Q: Can I filter Fusioo data in LlamaIndex?

You can use the allowedtools filter to restrict which parts of the workspace the agent accesses. This limits the scope of your RAG application to only the apps you specify.

Q: How do I track record counts for LlamaIndex?

Call getapprecordcount to monitor your data volume. This helps you manage your index size and API limits effectively.

Index your Fusioo workspace data into LlamaIndex to build RAG applications that answer questions grounded in live records.

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Connect Fusioo MCP to LlamaIndex

Create your Vinkius account to connect Fusioo 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 Fusioo with LlamaIndex

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Semantic search for Fusioo in LlamaIndex

Use `list_app_records` to pull data into your vector store. Your index becomes a living map of your workspace content. Queries return results based on actual record details. You get precise answers instead of generic guesses.

Retrieve record metadata as context

Call `get_record_details` to fetch specific metadata during the query process. LlamaIndex then uses this context to build a more accurate response. This bridges the gap between raw data and actionable knowledge. Your agent understands the underlying structure of every record it retrieves.

Manage custom app structures

Expose your `get_app_schema` output to the agent for better data handling. It learns the specific fields and constraints of your apps. The agent uses this schema to filter and sort information before indexing. This keeps your knowledge base clean and relevant.

Setup guide

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

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Common questions about Fusioo MCP in LlamaIndex

Initialize the BasicMCPClient and use the McpToolSpec to convert tools into a list. Pass these to your agent, which then queries the API to populate your vector index.

Yes. You can trigger `update_app_record` through the agent once it has analyzed your indexed data. It allows for a loop of search, analyze, and modify.

You can use the allowed_tools filter to restrict which parts of the workspace the agent accesses. This limits the scope of your RAG application to only the apps you specify.

Call `get_app_record_count` to monitor your data volume. This helps you manage your index size and API limits effectively.

All ingested records are processed in memory and indexed locally within your vector store. We never cache your workspace records on our servers.

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