temporal-mcp

temporal-mcp

An MCP server for debugging Temporal workflows, enabling LLM-assisted inspection of workflow executions, detailed workflow info, and event history.

Category
Visit Server

README

Temporal MCP Server

An MCP (Model Context Protocol) server for debugging Temporal workflows. This server enables LLM-assisted debugging by exposing Temporal workflow inspection tools.

Features

  • list_workflows - List workflow executions with optional query filter
  • describe_workflow - Get detailed info about a specific workflow
  • get_workflow_history - Fetch event history for debugging

Requirements

  • Python 3.11+
  • uv for dependency management
  • A running Temporal server (local or cloud)

Installation

# Clone the repository
git clone <repo-url>
cd temporal-mcp

# Create virtual environment and install
uv venv
source .venv/bin/activate
uv pip install -e ".[dev]"

Configuration

Set environment variables to configure the Temporal connection:

Variable Description Default
TEMPORAL_ADDRESS Temporal server address localhost:7233
TEMPORAL_NAMESPACE Temporal namespace default
TEMPORAL_TLS_CERT Path to TLS certificate (for Cloud) -
TEMPORAL_TLS_KEY Path to TLS key (for Cloud) -
TEMPORAL_API_KEY API key (for Cloud) -

Docker

Connect to Temporal Server

If you have Temporal running (locally or remotely):

# Connect to Temporal on host machine
docker compose up

# Or specify a custom address
TEMPORAL_ADDRESS=my-temporal:7233 docker compose up

Connect to Temporal Cloud

For Temporal Cloud with mTLS certificates:

# Place your certificates in a certs/ directory, then:
docker compose up
# After uncommenting the TLS environment variables in docker-compose.yml

Or with API key:

TEMPORAL_ADDRESS=your-ns.tmprl.cloud:7233 \
TEMPORAL_NAMESPACE=your-ns \
TEMPORAL_API_KEY=your-key \
docker compose up

Local Development (without Docker)

Install and run directly with Python:

For Temporal Cloud, set the appropriate environment variables:

export TEMPORAL_ADDRESS="your-namespace.tmprl.cloud:7233"
export TEMPORAL_NAMESPACE="your-namespace"
export TEMPORAL_API_KEY="your-api-key"

Or with TLS certificates:

export TEMPORAL_ADDRESS="your-namespace.tmprl.cloud:7233"
export TEMPORAL_NAMESPACE="your-namespace"
export TEMPORAL_TLS_CERT="/path/to/cert.pem"
export TEMPORAL_TLS_KEY="/path/to/key.pem"

Usage

With Cursor

Add to your Cursor MCP settings (~/.cursor/mcp.json):

{
  "mcpServers": {
    "temporal": {
      "command": "uv",
      "args": ["run", "temporal-mcp"],
      "cwd": "/path/to/temporal-mcp",
      "env": {
        "TEMPORAL_ADDRESS": "localhost:7233",
        "TEMPORAL_NAMESPACE": "default"
      }
    }
  }
}

Standalone

temporal-mcp

Available Tools

list_workflows

List workflow executions with optional filtering.

list_workflows(query="", limit=10)
  • query: Optional Temporal list filter syntax (e.g., WorkflowType="MyWorkflow" AND ExecutionStatus="Running")
  • limit: Maximum workflows to return (default 10, max 100)

describe_workflow

Get detailed information about a specific workflow.

describe_workflow(workflow_id, run_id="")
  • workflow_id: The workflow ID to describe
  • run_id: Optional run ID (uses latest if not specified)

get_workflow_history

Fetch the event history for a workflow execution.

get_workflow_history(workflow_id, run_id="", max_events=100)
  • workflow_id: The workflow ID
  • run_id: Optional run ID (uses latest if not specified)
  • max_events: Maximum events to return (default 100, max 1000)

Development

Setup

uv venv
source .venv/bin/activate
uv pip install -e ".[dev]"

Commands

# Format code
black src tests

# Lint
ruff check src tests

# Type check
mypy src

# Run tests
pytest

# Run all checks
black src tests && ruff check src tests && mypy src && pytest

Project Structure

temporal-mcp/
├── pyproject.toml          # Project config and dependencies
├── Dockerfile
├── docker-compose.yml       # Docker setup for MCP server
├── README.md
├── src/temporal_mcp/
│   ├── __init__.py
│   ├── server.py           # MCP server and tool definitions
│   ├── client.py           # Temporal client wrapper
│   ├── config.py           # Environment-based configuration
│   └── models.py           # Pydantic models
├── tests/
│   ├── conftest.py         # Test fixtures
│   ├── test_config.py
│   ├── test_client.py
│   └── test_server.py
└── docs/
    └── PLAN.txt

License

MIT

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured