Plecto MCP Server for LlamaIndexGive LlamaIndex instant access to 11 tools to Create Data Registration, Get Dashboard, Get Employee, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Plecto 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 App Connector for LlamaIndex
The Plecto app connector for LlamaIndex is a standout in the Productivity category — giving your AI agent 11 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 Plecto. "
"You have 11 tools available."
),
)
response = await agent.run(
"What tools are available in Plecto?"
)
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 Plecto MCP Server
Connect your Plecto account to any AI agent and simplify your KPI tracking, performance management, and dashboard orchestration through natural conversation.
LlamaIndex agents combine Plecto tool responses with indexed documents for comprehensive, grounded answers. Connect 11 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
- Data Registrations — List all data entries for any data source, retrieve detailed metadata, and monitor real-time values
- Direct Execution — Create new data registrations programmatically directly from your agent to feed your dashboards
- KPI Dashboards — Query all configured KPI dashboards and retrieve detailed metadata to monitor performance
- Team Coordination — List organizational teams and employees to manage access and resource allocation
- Data Sources — Query all configured data sources to choose the right context for each interaction
The Plecto MCP Server exposes 11 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.
All 11 Plecto tools available for LlamaIndex
When LlamaIndex connects to Plecto through Vinkius, your AI agent gets direct access to every tool listed below — spanning kpi-tracking, performance-management, real-time-data, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Add a new data entry
Get details for a specific dashboard
Get details for a specific employee
Get details for a specific data registration
List account employees
List Plecto registrations
List Plecto data sources
List all KPI formulas
List Plecto dashboards
List teams
List all widgets on a dashboard
Connect Plecto to LlamaIndex via MCP
Follow these steps to wire Plecto into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the 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 Plecto MCP Server
LlamaIndex provides unique advantages when paired with Plecto through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Plecto tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Plecto tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Plecto, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Plecto tools were called, what data was returned, and how it influenced the final answer
Plecto + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Plecto MCP Server delivers measurable value.
Hybrid search: combine Plecto real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Plecto 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 Plecto for fresh data
Analytical workflows: chain Plecto queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Plecto in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Plecto immediately.
"List all my KPI dashboards in Plecto."
"Show me the sales leaderboard for the current month with all team member performance metrics."
"Register a new data point for Sarah Chen with $45,000 in closed deals today on the Revenue data source."
Troubleshooting Plecto MCP Server with LlamaIndex
Common issues when connecting Plecto to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpPlecto + LlamaIndex FAQ
Common questions about integrating Plecto MCP Server with LlamaIndex.