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How to Use the Dynamo Software MCP in LlamaIndex

Index your Dynamo Software records into LlamaIndex to build a searchable knowledge base for your firm.

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LlamaIndex

Connect Dynamo Software MCP to LlamaIndex

Create your Vinkius account to connect Dynamo Software 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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Semantic search for funds

Use `search_investment_funds` to pull data into your vector index for semantic retrieval. Your LLM can answer questions about fund categories based on the live data it indexed. This turns your static API results into a queryable memory. You'll get precise answers grounded in your actual account records rather than guessing.

Index fund details

Call `get_fund_details` and feed the output directly into your RAG pipeline. LlamaIndex stores these records so your agent can compare current fund settings against past configurations. Your knowledge base stays updated as you add new funds. Just run the ingestion loop, and the index reflects your latest Dynamo Software state.

Query historical activities

Retrieve `list_latest_dynamo_activities` and index the logs for long-term pattern analysis. You can ask your agent what changed in a portfolio over the last month and get a cited response. This approach gives you a historical record of all platform interactions. It's built for deep dives into past investment decisions.

Setup guide

Set up Dynamo Software MCP in LlamaIndex

Prerequisites

  • Python 3.10+ installed
  • llama-index-tools-mcp package
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Install dependencies

    Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.

  2. 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. 3

    Convert to LlamaIndex tools

    Call mcp_tool_spec.to_tool_list_async() to convert all Dynamo Software MCP tools into native FunctionTool objects that any LlamaIndex agent can use.

  4. 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 Dynamo Software tools.",
)
response = await agent.run("List recent Dynamo Software data")

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Dynamo Software. 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 Dynamo Software MCP in LlamaIndex

You initialize the McpToolSpec and pass the tools to your agent. This maps the API data into a format your index can ingest and search.
It can. After the server pulls the fund data, LlamaIndex turns those results into vector embeddings for natural language questioning.
Yes, by indexing your portfolio lists, you allow the agent to reason about your entire investment structure in one go.
The server itself is ephemeral. Only your local vector store keeps the indexed information after the session ends.
The server uses a zero-trust model to isolate your fund details. No data persists outside your authorized AI client session.

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