How to Use the Geometry Calculator MCP in LlamaIndex

Q: Can I filter Geometry Calculator tools in LlamaIndex?

Yes. You can use the allowedtools filter to restrict which functions your agent can access. This keeps your agent focused on specific spatial tasks without cluttering the toolset.

Turn spatial results into searchable knowledge. Index your Geometry Calculator outputs directly into LlamaIndex vector stores.

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Connect Geometry Calculator MCP to LlamaIndex

Create your Vinkius account to connect Geometry Calculator 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 Geometry Calculator with LlamaIndex

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Claude

Perplexity

Index geometry results in LlamaIndex

Every calculation from `calculate_2d_area` or `calculate_3d_volume` can be stored directly in your vector index. You aren't just doing math; you're building a searchable history of your spatial data. Future queries can look back at these results. If you need to recall the volume of a cylinder calculated last week, your agent searches the index instead of re-running the operation.

Ground your RAG with precise math

Use `calculate_distance` to generate ground-truth coordinates for your RAG pipeline. By indexing these values, you ensure your agent's answers are based on exact math rather than hallucinated estimates. It bridges the gap between raw data and semantic understanding. Your agent retrieves the distance, understands the context, and provides an answer that is technically accurate.

Automated MCP tool ingestion

Use the tool spec to pull all three functions into your agent effortlessly. LlamaIndex handles the conversion, so your Geometry Calculator tools are ready for semantic search immediately. You avoid manual configuration. The tool list is generated dynamically, ensuring your agent always has access to the latest version of the geometry primitives.

Setup guide

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

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Common questions about Geometry Calculator MCP in LlamaIndex

By indexing the output of the tools, your agent retrieves verified geometric data instead of guessing. This creates a foundation of facts that your RAG system can query for precise answers.

Yes. You can use the allowed_tools filter to restrict which functions your agent can access. This keeps your agent focused on specific spatial tasks without cluttering the toolset.

All math operations happen locally before being indexed. Your raw coordinates are never transmitted to a third party, keeping your spatial datasets completely isolated.

Once indexed, you use standard semantic search to find previous calculations. The vector store treats your tool outputs as searchable knowledge, allowing for quick retrieval of historical spatial data.

It does. The tool spec supports async execution, meaning your RAG pipeline can perform geometry calculations in parallel with other data retrieval tasks.

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