Numbers API MCP Server for LlamaIndex 5 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Numbers API as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Numbers API. "
"You have 5 tools available."
),
)
response = await agent.run(
"What tools are available in Numbers API?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Numbers API MCP Server
Equip your AI agent with interesting facts and historical context for any number or date via the Numbers API. This server provides instant access to trivia, mathematical properties, and historical events associated with specific numbers and years. Your agent can retrieve date-specific facts, audit mathematical patterns, and provide random interesting context for numerical data without any manual search. Whether you are adding color to a presentation or verifying historical timelines, your agent acts as a dedicated numerical encyclopedia through natural conversation.
LlamaIndex agents combine Numbers API tool responses with indexed documents for comprehensive, grounded answers. Connect 5 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Trivia Discovery — Retrieve fun and unusual facts for any integer or random number.
- Math Intelligence — Access technical mathematical properties and interesting patterns for specific numbers.
- Date Auditing — Fetch historical events that occurred on any specific month and day of the year.
- Yearly Context — Retrieve significant historical milestones and facts for any given year.
- Random Inspiration — Get a completely random fact across all categories to discover new knowledge.
The Numbers API MCP Server exposes 5 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Numbers API to LlamaIndex via MCP
Follow these steps to integrate the Numbers API MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 5 tools from Numbers API
Why Use LlamaIndex with the Numbers API MCP Server
LlamaIndex provides unique advantages when paired with Numbers API through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Numbers API tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Numbers API tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Numbers API, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Numbers API tools were called, what data was returned, and how it influenced the final answer
Numbers API + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Numbers API MCP Server delivers measurable value.
Hybrid search: combine Numbers API real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Numbers API to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Numbers API for fresh data
Analytical workflows: chain Numbers API queries with LlamaIndex's data connectors to build multi-source analytical reports
Numbers API MCP Tools for LlamaIndex (5)
These 5 tools become available when you connect Numbers API to LlamaIndex via MCP:
get_date_fact
Get a fact about a date
get_math_fact
Get a mathematical fact about a number
get_random_fact
Get a random fact
get_trivia_fact
Get a trivia fact about a number
get_year_fact
Get a fact about a year
Example Prompts for Numbers API in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Numbers API immediately.
"Tell me a trivia fact about the number 42."
"What happened on October 24th in history?"
"Give me a random math fact."
Troubleshooting Numbers API MCP Server with LlamaIndex
Common issues when connecting Numbers API to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpNumbers API + LlamaIndex FAQ
Common questions about integrating Numbers API MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Numbers API with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Numbers API to LlamaIndex
Get your token, paste the configuration, and start using 5 tools in under 2 minutes. No API key management needed.