Retable MCP Server for LlamaIndexGive LlamaIndex instant access to 10 tools to Check Retable Status, Create Record, Delete Record, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Retable 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 Retable app connector for LlamaIndex is a standout in the Productivity category — giving your AI agent 10 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 Retable. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Retable?"
)
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 Retable MCP Server
Connect your Retable account to any AI agent and manage your spreadsheet data through natural conversation.
LlamaIndex agents combine Retable 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
- Project Management — List and inspect projects
- Table Access — Browse tables and view schemas
- Record Operations — List, get, create, update, and delete records
- Health Check — Verify API connectivity
The Retable 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.
All 10 Retable tools available for LlamaIndex
When LlamaIndex connects to Retable through Vinkius, your AI agent gets direct access to every tool listed below — spanning relational-database, spreadsheet-automation, collaborative-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.
Verify API connectivity
Create a new record
Delete a record
Get project details
Get record details
Get table details
List all projects
List records in a table
List tables in a project
Update a record
Connect Retable to LlamaIndex via MCP
Follow these steps to wire Retable 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 Retable MCP Server
LlamaIndex provides unique advantages when paired with Retable through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Retable tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Retable tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Retable, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Retable tools were called, what data was returned, and how it influenced the final answer
Retable + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Retable MCP Server delivers measurable value.
Hybrid search: combine Retable real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Retable 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 Retable for fresh data
Analytical workflows: chain Retable queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Retable in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Retable immediately.
"List all my Retable projects."
"Show all records in table tbl_001."
"Add a new record to table tbl_001 with name 'NewClient' and status 'New'."
Troubleshooting Retable MCP Server with LlamaIndex
Common issues when connecting Retable to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpRetable + LlamaIndex FAQ
Common questions about integrating Retable MCP Server with LlamaIndex.