Temporal MCP Server
Enables AI assistants to manage Temporal workflows, schedules, and workflow executions through a standardized interface.
README
Temporal MCP Server
Overview
This is a Model Context Protocol (MCP) server that provides tools for interacting with Temporal workflow orchestration. It enables AI assistants and other MCP clients to manage Temporal workflows, schedules, and workflow executions through a standardized interface. The server supports both local and remote Temporal instances.
Read more on the Temporal Code Exchange
Distributions
- PyPI - https://pypi.org/project/temporal-mcp-server/
- Docker - https://hub.docker.com/r/mcp/temporal
Tools
Workflow Execution
start_workflow- Start a new Temporal workflow execution with specified parameters, workflow ID, and task queueget_workflow_result- Retrieve the result of a completed workflow executiondescribe_workflow- Get detailed information about a workflow execution including status, timing, and metadatalist_workflows- List workflow executions based on a query filter with pagination support (limit/skip)get_workflow_history- Retrieve the complete event history of a workflow execution
Workflow Control
query_workflow- Query a running workflow for its current state without affecting executionsignal_workflow- Send a signal to a running workflow to change its behavior or provide datacancel_workflow- Request cancellation of a running workflow executionterminate_workflow- Forcefully terminate a workflow execution with a reasoncontinue_as_new- Signal a workflow to continue as new (restart with new inputs while preserving history link)
Batch Operations
batch_signal- Send a signal to multiple workflows matching a query (configurable batch size)batch_cancel- Cancel multiple workflows matching a query (configurable batch size)batch_terminate- Terminate multiple workflows matching a query with a specified reason (configurable batch size)
Schedule Management
create_schedule- Create a new schedule for periodic workflow execution using cron expressionslist_schedules- List all schedules with pagination support (limit/skip)pause_schedule- Pause a schedule to temporarily stop workflow executionsunpause_schedule- Resume a paused scheduledelete_schedule- Permanently delete a scheduletrigger_schedule- Manually trigger a scheduled workflow immediately
Temporal Documentation
For more information about Temporal, refer to the official Temporal documentation:
- Temporal Documentation: https://docs.temporal.io/
- Workflows: https://docs.temporal.io/workflows
- Activities: https://docs.temporal.io/activities
- Python SDK: https://docs.temporal.io/dev-guide/python
VS Code MCP Config
Add a .vscode/mcp.json file to your workspace. Choose the approach that fits your setup.
Docker (environment variables)
Recommended when running via Docker. Configuration is passed through environment variables.
{
"servers": {
"temporal": {
"command": "docker",
"args": [
"run", "-i", "--rm",
"-e", "TEMPORAL_HOST",
"-e", "TEMPORAL_NAMESPACE",
"-e", "TEMPORAL_TLS_ENABLED",
"-e", "TEMPORAL_TLS_CLIENT_CERT_PATH",
"-e", "TEMPORAL_TLS_CLIENT_KEY_PATH",
"-e", "TEMPORAL_API_KEY",
"mcp/temporal"
],
"env": {
"TEMPORAL_HOST": "localhost:7233",
"TEMPORAL_NAMESPACE": "default",
"TEMPORAL_TLS_ENABLED": "false",
"TEMPORAL_TLS_CLIENT_CERT_PATH": "/path/to/client.pem",
"TEMPORAL_TLS_CLIENT_KEY_PATH": "/path/to/client.key",
"TEMPORAL_API_KEY": "your-api-key"
}
}
}
}
Python via uvx (CLI arguments)
Recommended when running from PyPI via uvx. No local install required — uvx fetches and runs the package automatically. Configuration is passed as CLI arguments.
{
"servers": {
"temporal": {
"command": "uvx",
"args": [
"temporal-mcp-server",
"--host", "localhost:7233",
"--namespace", "default",
"--tls-enabled", "false",
"--tls-cert", "/path/to/client.pem",
"--tls-key", "/path/to/client.key",
"--api-key", "your-api-key"
]
}
}
}
Configuration Options
| Option | CLI Argument | Environment Variable | Default |
|---|---|---|---|
| Temporal host | --host |
TEMPORAL_HOST |
localhost:7233 |
| Namespace | --namespace |
TEMPORAL_NAMESPACE |
default |
| TLS | --tls-enabled |
TEMPORAL_TLS_ENABLED |
auto-detect |
| mTLS cert path | --tls-cert |
TEMPORAL_TLS_CLIENT_CERT_PATH |
— |
| mTLS key path | --tls-key |
TEMPORAL_TLS_CLIENT_KEY_PATH |
— |
| API key | --api-key |
TEMPORAL_API_KEY |
— |
CLI arguments take precedence over environment variables. When TEMPORAL_API_KEY is set, TLS is enabled automatically. When mTLS cert/key paths are provided, TLS is also enabled automatically.
Development
Running Tests
Install development dependencies:
pip install -r requirements-dev.txt
Run the test suite:
pytest test.py -v
Building the Docker Image
docker build -t mcp/temporal:latest .
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