Bonusly MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Bonusly 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 Bonusly. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Bonusly?"
)
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 Bonusly MCP Server
Connect your Bonusly employee recognition account to any AI agent and orchestrate your team culture and reward workflows through natural conversation.
LlamaIndex agents combine Bonusly tool responses with indexed documents for comprehensive, grounded answers. Connect 10 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
- Peer Recognition — Instantly give bonuses to colleagues with custom reasons and hashtags representing company values.
- Bonus Oversight — List recent bonuses and retrieve detailed information for specific recognition events.
- User & Profile Management — Access employee profiles and check your own point balance and history.
- Reward Tracking — Monitor recent redemptions to see how your team is spending their earned points.
- Culture Insights — List company values, popular hashtags, and view the real-time recognition leaderboard.
The Bonusly MCP Server exposes 10 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 Bonusly to LlamaIndex via MCP
Follow these steps to integrate the Bonusly 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 10 tools from Bonusly
Why Use LlamaIndex with the Bonusly MCP Server
LlamaIndex provides unique advantages when paired with Bonusly through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Bonusly tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Bonusly tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Bonusly, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Bonusly tools were called, what data was returned, and how it influenced the final answer
Bonusly + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Bonusly MCP Server delivers measurable value.
Hybrid search: combine Bonusly real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Bonusly 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 Bonusly for fresh data
Analytical workflows: chain Bonusly queries with LlamaIndex's data connectors to build multi-source analytical reports
Bonusly MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Bonusly to LlamaIndex via MCP:
get_bonus
Get details of a specific bonus
get_leaderboard
Get the recognition leaderboard
get_my_profile
Get the profile of the authenticated user
get_user
Get profile details for an employee
give_bonus
Give a recognition bonus to an employee
list_bonuses
List recent employee bonuses
list_company_values
List company values and hashtags
list_hashtags
List popular hashtags
list_redemptions
List recent reward redemptions
list_users
List all employees
Example Prompts for Bonusly in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Bonusly immediately.
"Give +10 to sarah@example.com for helping with the client presentation #teamwork."
"What is my current Bonusly balance?"
"Show the recent bonuses in the company."
Troubleshooting Bonusly MCP Server with LlamaIndex
Common issues when connecting Bonusly to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpBonusly + LlamaIndex FAQ
Common questions about integrating Bonusly 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 Bonusly 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 Bonusly to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.