Temporal MCP Server for LlamaIndex 7 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Temporal as an MCP tool provider through the 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 Temporal. "
"You have 7 tools available."
),
)
response = await agent.run(
"What tools are available in Temporal?"
)
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 Temporal MCP Server
Connect your Temporal Cloud (or self-hosted) cluster to any AI agent and bring the power of durable execution directly into your IDE or chat via natural conversation.
LlamaIndex agents combine Temporal tool responses with indexed documents for comprehensive, grounded answers. Connect 7 tools through the 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
- Workflows & Executions — List, filter, and inspect active, running, or completed workflow executions
- Workflow History — Retrieve the complete sequence of events, activities, and signals to debug failures
- Visibility Search — Run complex SQL-like queries using Temporal Visibility syntax to find specific runs
- Namespace Details — Check retention periods, configurations, and metadata of your operational namespace
- Schedules & Cron — Browse all recurring workflows and predict the next execution schedules
The Temporal MCP Server exposes 7 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 Temporal to LlamaIndex via MCP
Follow these steps to integrate the Temporal 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 7 tools from Temporal
Why Use LlamaIndex with the Temporal MCP Server
LlamaIndex provides unique advantages when paired with Temporal through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Temporal tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Temporal tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Temporal, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Temporal tools were called, what data was returned, and how it influenced the final answer
Temporal + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Temporal MCP Server delivers measurable value.
Hybrid search: combine Temporal real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Temporal 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 Temporal for fresh data
Analytical workflows: chain Temporal queries with LlamaIndex's data connectors to build multi-source analytical reports
Temporal MCP Tools for LlamaIndex (7)
These 7 tools become available when you connect Temporal to LlamaIndex via MCP:
get_namespace_details
Retrieves information about the current namespace
get_workflow_details
Retrieves details for a specific workflow execution
get_workflow_history
Retrieves the event history for a workflow execution
list_schedules
Lists all workflow schedules
list_search_attributes
Lists custom search attributes available in the namespace
list_workflows
Returns workflow IDs, run IDs, and statuses. Lists all workflow executions in the configured namespace
search_workflows
g., WorkflowType="MyType" AND Status="Running"). Search workflows using Temporal Visibility Query syntax
Example Prompts for Temporal in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Temporal immediately.
"Show me the last 5 workflows that failed or panicked in the default namespace."
"Explain the exact execution history for workflow 'GenerateInvoice-102'."
"List all active schedules and tell me when the database backup is due."
Troubleshooting Temporal MCP Server with LlamaIndex
Common issues when connecting Temporal to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpTemporal + LlamaIndex FAQ
Common questions about integrating Temporal 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 Temporal 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 Temporal to LlamaIndex
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.