Temporal MCP for AI. Debug durable workflows right from your chat.

Q: How do I find a specific failed workflow using getworkflowdetails?

You first need the Run ID. Use listworkflows or searchworkflows to find the correct Run ID, and then pass that ID to getworkflowdetails. This gives you the high-level status before digging into history.

Q: Does getnamespacedetails tell me about individual workflows?

No. It only provides metadata about the namespace itself—stuff like its retention policy and configuration settings. Use listworkflows for actual workflow data.

Q: What's the difference between listworkflows and searchworkflows?

Simple: listworkflows gives you a raw, basic list of IDs and statuses in the namespace. searchworkflows lets you apply complex filters (like finding all 'Payment' workflows that failed last week).

Q: How do I check if my scheduled job is running?

First, run listschedules to see the schedule name. Then, use getworkflowdetails on a recent execution ID associated with that schedule to confirm its current operational status.

Q: Before running a complex query with searchworkflows, how can I find out which attributes are available?

Run listsearchattributes first. This tool returns every custom attribute defined in your namespace. Knowing these fields ensures your search syntax is correct and prevents failed queries.

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

Connect to your AI in seconds.

Temporal MCP Server monitors and manages distributed workflows in Temporal Cloud. Your AI client can list active runs, search for failed executions using visibility syntax, or retrieve the entire event history to debug complex processes instantly.

What your AI can do

Get workflow history

Retrieves the full, detailed event history log for any specific workflow run to track its entire lifecycle.

Get namespace details

Retrieves core metadata, including the configured retention period, for your current namespace.

Get workflow details

Fetches high-level status and configuration details for a single workflow execution ID.

+ 4 more capabilities included

View Workflow Status

List all workflow runs, filtering by status (running, completed, failed) using list_workflows.

Inspect Specific Runs

Pull detailed information for a single workflow execution with get_workflow_details.

Debug Execution Failures

Get the full chronological sequence of events, activities, and signals using get_workflow_history.

Search Complex Runs

Run advanced queries (like SQL) across your runs using Temporal Visibility syntax via search_workflows.

Audit Namespace Settings

Check the configuration, retention periods, and metadata of your operational namespace with get_namespace_details.

Monitor Scheduled Jobs

List all recurring workflows using list_schedules and predict their next run times.

Ask an AI about this

Included with Plan

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AI Agent

Temporal MCP Server: 7 Tools for Durable Workflows

These tools let you manage every aspect of your distributed system's execution state—from listing basic statuses to running deep, query-based historical audits.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using Temporal on Vinkius

Get Workflow History

Retrieves the full, detailed event history log for any specific workflow run to track its entire lifecycle.

Get Namespace Details

Retrieves core metadata, including the configured retention period, for your current...

Get Workflow Details

Fetches high-level status and configuration details for a single workflow execution...

List Schedules

Returns a list of all defined recurring workflows and when they are scheduled to run...

List Search Attributes

Shows you what custom attributes are available for searching within the namespace...

List Workflows

Lists all workflow executions in the configured namespace, providing their IDs and current status (running, failed, etc.).

Search Workflows

Allows running complex queries across runs using Temporal Visibility syntax to filter results by type or status.

Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

Claude AI

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

Start a conversation

Open a new chat. The Temporal integration is available immediately — no restart needed.

Antigravity

Configure Agent Environment

Open your Antigravity agent's workspace configuration or mcp-servers.json file.

Bind the Endpoint

Add the Vinkius endpoint URL to your agent's MCP connections list:

"mcp_servers": {
  "temporal": {
    "serverUrl": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
  }
}

Provide your secure token in place of [YOUR_TOKEN_HERE] to ensure your agent requests are authenticated.

Execute

Start your Antigravity session. The agent will autonomously discover and utilize the Temporal tools with full Vinkius guardrails applied.

VS Code Copilot

⚡

One-Click Install (Recommended)

In your Vinkius Dashboard, simply click the Add to VS Code button for this server. We'll automatically configure your local workspace.

Or configure manually

Open MCP Settings

Open VS Code, press Ctrl/Cmd + Shift + P, and search for GitHub Copilot: MCP Servers.

Add Server Config

Add the Vinkius endpoint configuration to your mcp-servers.json file:

"temporal": {
  "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}

Ensure you replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.

LangChain

Install Dependencies

Install the LangChain MCP adapters for your environment:

pip install langchain-mcp-adapters

Connect the Server

Use the SSEClient in LangChain to connect to the Vinkius managed endpoint:

from langchain_mcp_adapters.client import SSEClient

# Connect to Vinkius
client = SSEClient(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
tools = client.get_tools()

CrewAI

Define the Tool

Load the Vinkius MCP tools into your CrewAI agents:

from crewai import Agent
from mcp_crewai import MCPTool

# Connect securely to Vinkius
vinkius_tools = MCPTool(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

# Assign to Agent
researcher = Agent(
    role='Data Researcher',
    tools=vinkius_tools.get_all()
)

Execute Task

Run your CrewAI process. The agent will autonomously route tasks to the Vinkius managed server.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

Import from OpenAPI, Swagger, or YAML specs
Create Agent Skills with progressive disclosure
Deploy to edge with MCPFusion framework
Built in DLP, auth, and compliance on every call
Real time usage dashboard and cost metering
Publish to catalog or keep private

Start building

Make Your AI Do More

Start with Temporal, then connect any of our 5,100+ other servers whenever your AI needs more. One click, no limits.

Use this MCP plus 5,100+ others, all in one place
Add new capabilities to your AI anytime you want
Every connection is secured and compliant automatically
Track usage and costs across all your servers
Works with Claude, ChatGPT, Cursor, and more
New servers added to the catalog every week

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Temporal. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Sandboxed per request

Zero-Trust Proxy

No stored credentials

DLP Enforced

Policy on every call

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EU data residency

Token Compression

~60% cost reduction

Your data is protected. See how we built it.

Works with Claude, ChatGPT, Cursor, and more

The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.

This connection provides 7 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.

Debugging complex processes shouldn't require a dozen dashboard clicks.

Right now, when something breaks in your distributed system, you open the Temporal UI. You select the namespace, filter by 'Failed,' scroll through dozens of runs, and then for each run ID, you have to click another tab—the history view—just to see if it timed out or crashed on a specific activity.

With this MCP server, your agent handles all that clicking. You just ask: 'What went wrong with the payment workflow?' The server executes `search_workflows` and then automatically provides the full event log using `get_workflow_history`. You get the answer in plain text, without leaving your chat window.

Temporal MCP Server: Get execution history via agent.

You eliminate the need to remember which dashboard holds which piece of metadata. No more toggling between 'Namespaces' view, then running a separate query for 'Schedules,' and finally opening the run details in another tab just to check retention policies.

Everything is available through natural conversation. It turns complex operational knowledge into simple, callable functions. You can audit everything—from `list_workflows` status checks to deep dives with `get_workflow_history`—without ever touching the UI.

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What your AI can actually do with this

This MCP Server connects your AI client directly to Temporal Cloud's execution engine. It lets you treat complex workflow management data—the kind SREs use every day—like simple API calls right from your chat window. You don't gotta open the clunky UI or run command line tools; your agent handles it all.

Understanding Your Workflow Environment

You can check the operational state of your system first. The get_namespace_details tool pulls core metadata for your current namespace, letting you verify things like the configured retention period and overall settings. Before running any searches, use list_search_attributes to see exactly what custom attributes are available in the namespace; this helps structure your queries correctly.

Monitoring Runs and Status

Need a quick status check? The list_workflows tool gives you an immediate roster of all workflow executions in the configured namespace, listing their IDs and current status—whether they're running, completed, or failed. If you're tracking scheduled jobs, list_schedules returns a list of every defined recurring workflow, showing when each one is slated to run next.

To get specific details on any single run, use get_workflow_details; this fetches the high-level status and configuration data for just that one workflow execution ID.

Advanced Search and Querying

When you gotta dig deep, the system provides advanced querying options. The search_workflows tool lets you run complex queries across your entire history using Temporal Visibility syntax. You can filter results by specific types or statuses to narrow down huge datasets fast. If you're not sure what parameters work for a search, check out list_search_attributes first.

Debugging Failures and Tracking History

Debugging is where this thing shines. When a workflow fails, the single most valuable thing is the full sequence of events. The get_workflow_history tool retrieves the complete event history log for any specific run ID; you'll see every activity, signal, and change in state that happened during its entire lifecycle, letting you pinpoint exactly where things went wrong.

For even broader visibility than a single failure, you can use search_workflows to find groups of failed runs or successful batches. The combination of tools means your agent handles the full audit trail: check namespace settings with get_namespace_details, list all running jobs using list_workflows, and pull the entire chronological event record for deep debugging with get_workflow_history.

It's built for platform engineers who need answers, period.

Built · Hosted · Managed by Vinkius Temporal MCP Server - Manage Workflow Execution History

Server ID 019d7611-5de9-7192-8ef6-043ea1fc3fd7

Vinkius Inspector

Compliance Grade A+

Score 100/100

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Here's how it actually works

The bottom line is: you talk to your AI agent like it's a dashboard, but the server does the heavy lifting by connecting directly to Temporal's core API.

Subscribe to the server, then enter your Temporal Address, Namespace, and API Key (or cert path).

Your AI client executes a command—for instance, 'Show me all failed payment workflows.'

The agent uses the appropriate tool (search_workflows) to query the cluster state and returns the actionable data set.

What Changes When You Connect

Instant debugging: Instead of jumping into the Temporal UI, you can ask the agent to run get_workflow_history and immediately see every event that happened during a failure. That saves time.

Targeted searching: Need to find all runs that failed last week? Use search_workflows with specific criteria (e.g., Status="Failed") instead of manually filtering huge lists.

Know your limits: Run get_namespace_details anytime to check the retention period or configuration metadata, making sure you stay compliant without logging into a separate console.

Manage recurring jobs: Use list_schedules to get a clean overview of every scheduled workflow and see exactly when the next critical job (like a nightly backup) is due.

Simple status checks: The list_workflows tool gives you a quick rundown of all active runs, letting you know if anything unusual—like an unexpected spike in failures—is happening right now.

See it in action

01 01

The Failed Payment Run

A customer reports their payment failed. The agent uses search_workflows to filter for 'Payment' workflows with a 'Failed' status. Then, it runs get_workflow_history on the resulting ID, pinpointing that the failure occurred specifically at the 'ChargeCreditCard' activity. Problem solved.

02 02

Auditing Namespace Drift

Platform Ops needs to ensure all development namespaces follow the same data retention rules. They call get_namespace_details for multiple namespaces, quickly confirming that every one has a 30-day limit set correctly. No manual checks needed.

03 03

Checking Next Maintenance Window

The team needs to know when the nightly database backup runs. They ask the agent to run list_schedules. The server immediately returns the scheduled ID and calculates that the next execution starts in 4 hours, allowing them to prepare.

04 04

Diagnosing a Stalled Pipeline

The data pipeline workflow hasn't updated. An engineer uses list_workflows to check status, finds an old run is 'Running', and then calls get_workflow_details. The details show the process timed out, allowing them to restart it immediately.

The honest tradeoffs

Checking every failure manually

Anti-pattern

A developer opens the Temporal UI, clicks 'Failed,' scrolls through 50 runs, and copies a few Run IDs to debug them one by one.

The Fix

Instead, ask your agent to search_workflows using criteria like Status="Failed" AND StartTime > "yesterday". This filters everything instantly so you only get the relevant failures.

Guessing namespace configs

Anti-pattern

Assuming a new team's namespace follows standard retention rules, potentially leading to data compliance violations.

The Fix

Always run get_namespace_details. This confirms the current configured metadata and retention period before you write any code that relies on those boundaries.

Sequential lookups for status

Anti-pattern

Calling list_workflows to get all IDs, then calling get_workflow_details for each ID sequentially.

The Fix

Use targeted tools. If you know the ID, use get_workflow_details. If you need a list, start with list_workflows, but if you need filtered results, jump straight to search_workflows.

Questions you might have

How do I find a specific failed workflow using get_workflow_details? +

You first need the Run ID. Use list_workflows or search_workflows to find the correct Run ID, and then pass that ID to get_workflow_details. This gives you the high-level status before digging into history.

Can I use search_workflows for anything other than failures? +

Yes. You can filter by any attribute Temporal tracks, like workflow type or start time. You must use the full Visibility Query syntax, which is what makes search_workflows powerful.

Does get_namespace_details tell me about individual workflows? +

No. It only provides metadata about the namespace itself—stuff like its retention policy and configuration settings. Use list_workflows for actual workflow data.

What's the difference between list_workflows and search_workflows? +

Simple: list_workflows gives you a raw, basic list of IDs and statuses in the namespace. search_workflows lets you apply complex filters (like finding all 'Payment' workflows that failed last week).

How do I check if my scheduled job is running? +

First, run list_schedules to see the schedule name. Then, use get_workflow_details on a recent execution ID associated with that schedule to confirm its current operational status.

Before running a complex query with `search_workflows`, how can I find out which attributes are available? +

Run list_search_attributes first. This tool returns every custom attribute defined in your namespace. Knowing these fields ensures your search syntax is correct and prevents failed queries.

What specific configuration details does `get_namespace_details` reveal about the cluster? +

It provides essential metadata, including the configured retention periods for logs and the current operational status of the namespace. This helps you audit consistency across your distributed systems.

When I use `get_workflow_history`, what does the returned data structure look like? +

The history returns a chronological sequence of events, including timestamps, activity names, and signal payloads. It doesn't just show status; it shows every step taken during execution.

Can my AI agent debug a failed Temporal workflow run directly? +

Yes. Instead of browsing the Temporal UI to manually dissect the execution, feed the workflow ID directly to your AI agent. It can seamlessly fetch the entire event history, identify the exact panic line or activity timeout, and immediately suggest code fixes within your IDE.

How complex can the visibility searches be via natural language? +

Very complex. Because your agent understands your codebase, you can ask 'Find all workflows of type ProcessPayment that failed in the last 2 hours'. The agent formulates the perfect SQL-like syntax for the backend, parses the matching pages, and surfaces exactly which transactions failed.

Can it read scheduled jobs and Cron jobs configurations inside Temporal? +

Absolutely. You can request a list of all active schedules mapped to your namespace. Your agent unpacks JSON configurations, showing definitions of workflow recurrence, enabling you to detect missing crons without interrupting your workflow.

Connect to your AI in seconds.

Get workflow history

Get namespace details

Get workflow details

Temporal MCP Server: 7 Tools for Durable Workflows

Make your AI actually useful.

Get Workflow History

Get Namespace Details

Get Workflow Details

List Schedules

List Search Attributes

List Workflows

Search Workflows

Security and governance baked right in.

Claude AI

Open Claude Settings

Add Custom Connector

Start a conversation

Claude Code

Open your terminal

Add the MCP Server

Start coding

Cursor

One-Click Install (Recommended)

Open Cursor Settings

Add New Server

Use in Composer

Antigravity

Configure Agent Environment

Bind the Endpoint

Execute

VS Code Copilot

One-Click Install (Recommended)

Open MCP Settings

Add Server Config

Windsurf

One-Click Install (Recommended)

Open Windsurf Settings

Add Server Endpoint

LangChain

Install Dependencies

Connect the Server

CrewAI

Define the Tool

Execute Task

Choose How to Get Started

Build Your Own

Make Your AI Do More

Works with Claude, ChatGPT, Cursor, and more

Debugging complex processes shouldn't require a dozen dashboard clicks.

Temporal MCP Server: Get execution history via agent.

What your AI can actually do with this

Understanding Your Workflow Environment

Monitoring Runs and Status

Advanced Search and Querying

Debugging Failures and Tracking History

Here's how it actually works

Who is this actually for?

What Changes When You Connect

See it in action

The Failed Payment Run

Auditing Namespace Drift

Checking Next Maintenance Window

Diagnosing a Stalled Pipeline

The honest tradeoffs

Checking every failure manually

Guessing namespace configs

Sequential lookups for status

When It Fits, When It Doesn't

Questions you might have