How to Use the Yida MCP in LlamaIndex

Q: What is the best way to query historical actions with Yida and LlamaIndex?

You can pass results from getinstancetimeline into the index. This lets you ask questions like, 'What happened to this record last Tuesday?' and get a grounded answer.

Q: Can I filter data when using Yida MCP Server with LlamaIndex?

Yes. The client supports an allowedtools filter, meaning you can limit the knowledge base to specific types of calls, like only fetching records for certain forms.

Q: What data types are available in Yida when using LlamaIndex?

The server gives access to user profiles (listusers), form definitions (getformschema), and the record details themselves. All of this is consumable by the index.

Build knowledge graphs from Yida MCP Server output using LlamaIndex.

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Connect Yida MCP to LlamaIndex

Create your Vinkius account to connect Yida 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 Yida with LlamaIndex

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Semantic Search on Forms with LlamaIndex

MCP tool output becomes indexed knowledge. You can query past system configurations by having the index ingest results from `list_forms` and `get_form_schema`. This means you won't hallucinate; your answers are grounded in actual Yida form data.

Historical Record Retrieval via LlamaIndex

Don't just retrieve data—make it searchable. The index can consume details from `get_record_details` and the timeline provided by `get_instance_timeline`. This turns raw API calls into a unified, queryable knowledge base.

System State Analysis with MCP Server

Use LlamaIndex to build RAG applications over system metadata. Querying the available workflows (`list_workflows`) or identifying records via `list_data_ids` means your AI client gets answers based on actual API data, not just general knowledge.

Setup guide

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

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Common questions about Yida MCP in LlamaIndex

The MCP Server output is indexed into a vector store. This lets the index combine live data (like user lists from `list_users`) with documents, allowing semantic search over both.

You can pass results from `get_instance_timeline` into the index. This lets you ask questions like, 'What happened to this record last Tuesday?' and get a grounded answer.

Yes. The client supports an `allowed_tools` filter, meaning you can limit the knowledge base to specific types of calls, like only fetching records for certain forms.

The server gives access to user profiles (`list_users`), form definitions (`get_form_schema`), and the record details themselves. All of this is consumable by the index.

The server touches user application records and forms. The indexed knowledge base lets you search across structured form data while maintaining a clear understanding of the source data type.

Use it with your favorite AI tools

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