Kippy MCP Server for LlamaIndexGive LlamaIndex instant access to 13 tools to List Annual Scores, List Appraisals, List Audit Logs, and more
GDPR Free for SubscribersLlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Kippy 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 for LlamaIndex
The Kippy MCP Server for LlamaIndex is a standout in the Productivity category — giving your AI agent 13 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
Geminiimport 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 Kippy. "
"You have 13 tools available."
),
)
response = await agent.run(
"What tools are available in Kippy?"
)
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 Kippy MCP Server
Connect your Kippy account to any AI agent and manage performance tracking through natural conversation.
LlamaIndex agents combine Kippy tool responses with indexed documents for comprehensive, grounded answers. Connect 13 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
- OKR Tracking — Browse objectives and key results with progress percentages
- Goal Management — Create, update, and track individual and team goals
- Performance Reviews — Access review cycles, feedback, and ratings
- Team Monitoring — Track team performance metrics and alignment
- Progress Reports — Generate performance summaries and trend analysis
The Kippy MCP Server exposes 13 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 13 Kippy tools available for LlamaIndex
When LlamaIndex connects to Kippy through Vinkius, your AI agent gets direct access to every tool listed below — spanning okr-tracking, performance-management, goal-setting, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.
List annual scores on Kippy
List annual performance metrics
List appraisals on Kippy
List performance reviews and appraisals
List audit logs on Kippy
List system audit logs
List competencies on Kippy
List skills and competency tracking
List feedback on Kippy
List feedback entries
List kpi scores on Kippy
List KPIs with their current scores
List kpis on Kippy
List all KPIs for the organization
List notes on Kippy
List comments and annotations
List project scores on Kippy
List projects with their current scores
List projects on Kippy
List organizational projects
List team scores on Kippy
List team performance scores
List teams on Kippy
List teams in the organization
List users on Kippy
List users in Kippy
Connect Kippy to LlamaIndex via MCP
Follow these steps to wire Kippy into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Kippy MCP Server
LlamaIndex provides unique advantages when paired with Kippy through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Kippy tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Kippy tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Kippy, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Kippy tools were called, what data was returned, and how it influenced the final answer
Kippy + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Kippy MCP Server delivers measurable value.
Hybrid search: combine Kippy real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Kippy 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 Kippy for fresh data
Analytical workflows: chain Kippy queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Kippy in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Kippy immediately.
"Show all OKRs for Q2 and the team members falling behind."
"Show the latest performance review cycle and ratings."
"Create a new goal for the Engineering team and track alignment."
Troubleshooting Kippy MCP Server with LlamaIndex
Common issues when connecting Kippy to LlamaIndex through Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpKippy + LlamaIndex FAQ
Common questions about integrating Kippy 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?
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