# Ephemer Ephemeral MCP server

Source: https://glimind.com/server/mcp-registry%2Fal.ephemer%2Fephemeral
Registry id: `mcp-registry/al.ephemer/ephemeral`
Status: live (checked 2026-10-27T04:11:42.146Z)

## Measurements (30 days)

- Uptime: 100%
- Checks: 245
- Outages (90 days): 0

## Install

```json
{
  "mcpServers": {
    "ephemer-ephemeral-mcp-server": {
      "type": "http",
      "url": "https://app.ephemer.al/mcp"
    }
  }
}
```

Claude Code:

```sh
claude mcp add --transport http ephemer-ephemeral-mcp-server https://app.ephemer.al/mcp
```

## Tools (19)

- `cancel_run`: Cancel a run that has not finished. Work already done is billed. Cancelling a finished run changes nothing.
- `create_run`: Start an AI agent run in an isolated sandbox and return the run (status queued) at once. Give a prompt, or the name of a saved workflow. Poll with get_run or bl
- `create_schedule`: Start a saved workflow on a timetable. Needs an administrator key. Each start is a run billed to the organization, with the cost cap given here (or the default)
- `delete_schedule`: Permanently delete a schedule. Needs an administrator key. Runs it already started are not affected. To stop it for a while, pause it with update_schedule inste
- `delete_workflow`: Permanently delete a saved workflow. Runs already started are not affected; schedules that use it stop being able to start runs until it is saved again.
- `get_run`: Read a run: status, output, error, cost and billing_pending. COST: while billing_pending is true (or the run is still going), cost_micros is PROVISIONAL and usu
- `get_schedule`: Read a schedule: timetable, time zone, input, cost cap, whether it is enabled, its next start and the outcome of its last start.
- `get_workflow`: Read a saved workflow's definition: description, prompt, model, files, connections, limits and its input_schema and output_schema. Credentials are never include
- `list_connections`: The organization's saved connections that a run may use, with type, allowed methods and tools. No URLs or secrets are returned. Reference one in create_run by n
- `list_files`: List the files saved in the organization: id, name, size, content type and creation time. Reference a file by id in a run's or workflow's files. Read-only; uplo
- `list_models`: Find models. Returns a compact list (id, name, context_length, input and output USD per million tokens, zero_data_retention where known), the total count and th
- `list_runs`: List the organization's runs, newest first, with a cursor for the next page. Each run has cost_final: when false, cost_micros is provisional (usually above the 
- `list_schedules`: List the organization's schedules: each starts a saved workflow on a cron timetable. Includes the next start, the last run and the last error.
- `list_workflows`: List the organization's saved workflows (reusable run definitions). Each entry has the workflow's name and, when set, its description, input_schema (the shape o
- `preview_schedule`: Check a cron expression and time zone and return the next five start times (UTC), without saving anything.
- `run_schedule`: Start the schedule's workflow now, outside its timetable, with the schedule's input and cost cap. Returns the queued run (follow it with wait_for_run); each cal
- `save_workflow`: Create a workflow, or replace the one with this name (saving the same definition again changes nothing more). A workflow is a reusable run definition: start it 
- `update_schedule`: Change a schedule; only the fields you give change. Needs an administrator key. Set enabled to false to pause it and to true to resume it (resuming clears the f
- `wait_for_run`: Wait until a run finishes (succeeded, failed, cancelled, interrupted or timed_out) or the wait ends, then return the run. After the run finishes it keeps waitin

Measured by Glimind (https://glimind.com): MCP handshake + tool list only, no tool is ever called. CC BY 4.0.