Spaceship MCP
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# Spaceship AI MCP Server
MCP server for [Spaceship AI](https://spaceshipai.io) — build, run, and manage AI agents directly from Claude Code, Cursor, VS Code, and Windsurf.
## Quick start
Don't want to manually configure your MCP server?
Run `spaceshipai@latest init` to set everything up automatically with one command:
```bash
npx spaceshipai@latest init
```
This works with Claude Code, Cursor, VS Code, and Windsurf. It will authenticate via your browser, create a Spaceship API key for you, and configure your editor automatically.
## Manual installation
If you prefer to configure manually, add the following to your IDE's MCP config file.
**Claude Code** — run in your terminal:
```bash
claude mcp add --scope user --transport stdio spaceship --env SPACESHIP_API_KEY=sk_live_... -- uvx spaceship-mcp
```
Or add to `~/.claude.json`:
```json
{
"mcpServers": {
"spaceship": {
"command": "uvx",
"args": ["spaceship-mcp"],
"env": {
"SPACESHIP_API_KEY": "sk_live_..."
}
}
}
}
```
**Cursor** — add to `~/.cursor/mcp.json`:
```json
{
"mcpServers": {
"spaceship": {
"command": "uvx",
"args": ["spaceship-mcp"],
"env": {
"SPACESHIP_API_KEY": "sk_live_..."
}
}
}
}
```
**VS Code** — add to `~/.vscode/mcp.json`:
```json
{
"servers": {
"spaceship": {
"command": "uvx",
"args": ["spaceship-mcp"],
"env": {
"SPACESHIP_API_KEY": "sk_live_..."
}
}
}
}
```
**Windsurf** — add to `~/.codeium/windsurf/mcp_config.json`:
```json
{
"mcpServers": {
"spaceship": {
"command": "uvx",
"args": ["spaceship-mcp"],
"env": {
"SPACESHIP_API_KEY": "sk_live_..."
}
}
}
}
```
Get your API key from [spaceshipai.io](https://spaceshipai.io) under **Settings → API Keys**.
## Tools
### Projects
| Tool | Description |
|------|-------------|
| `list_projects` | List all projects in your organization |
### Agents
| Tool | Description |
|------|-------------|
| `list_agents` | List agents, optionally filtered by project |
| `get_agent` | Get full details of a single agent including its system prompt and tools |
| `create_agent` | Create an agent — pass `description` for auto-generated system prompt |
| `update_agent` | Update name, prompt, or tools; re-scaffold by passing a new `description` |
| `delete_agent` | **Permanently** delete an agent and all its logs, memories, and threads |
### Running agents
| Tool | Description |
|------|-------------|
| `run_agent` | Start an async run; returns `execution_id` for polling |
| `get_run_status` | Poll status: `queued` → `running` → `completed` / `error` / `cancelled` |
| `get_run_logs` | Fetch the full chronological event log for a completed run |
| `list_executions` | List recent runs for an agent with status and duration |
| `test_agent` | Quick sync test — runs an agent and waits up to 15s for the result |
### Orchestrations
| Tool | Description |
|------|-------------|
| `list_orchestrations` | List orchestrations, optionally filtered by project |
| `get_orchestration` | Get full details of an orchestration including its members and tools |
| `run_orchestration` | Start an async orchestration run; returns `execution_id` |
| `test_orchestration` | Quick sync test — runs an orchestration and waits up to 15s for the result |
### Tools
| Tool | Description |
|------|-------------|
| `list_tools` | List built-in and custom tools available to attach to agents |
## Example prompts
Once installed, you can talk to your agents naturally in any supported IDE:
```
List my projects, then show me all agents in the "production" project.
```
```
Create an agent called "Support Bot" in project 12 that handles customer refund requests.
```
```
Run the "Data Processor" agent with the prompt "Summarize last week's sales data".
```
```
Check the status of execution abc-123 for agent xyz-456, then show me the logs.
```
```
Test the "Email Classifier" agent with "Is this email spam: win a free iPhone now!"
```
```
List my orchestrations in the "production" project, then run the "Data Pipeline" orchestration.
```
```
Test the "Research Team" orchestration with input {"topic": "AI safety"} and show me the result.
```
## Configuration
| Variable | Required | Default | Description |
|----------|----------|---------|-------------|
| `SPACESHIP_API_KEY` | Yes | — | Your API key (`sk_live_...`) |
| `SPACESHIP_API_URL` | No | `https://spaceshipai.io` | Override for local dev or staging |
## Development
```bash
python3 -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"
pytest tests/ -v
```
## License
MIT
TDQS
Scored across 16 tools
All tools have clearly distinct purposes: create vs delete vs get vs list for agents, orchestrations, etc. Even similar tools like get_run_logs and get_run_status target different aspects of runs (logs vs status). test_agent and run_agent differ in synchronous vs asynchronous execution. No ambiguity.
All tool names consistently follow the verb_noun pattern with underscores (e.g., create_agent, get_run_status, list_projects). No mixing of camelCase or other styles. Very predictable.
16 tools is appropriate for a platform managing agents and orchestrations. It covers essential operations without being overwhelming. Each tool earns its place.
The tool set covers agent lifecycle (CRUD), run management (run, test, status, logs), orchestration operations (list, get, run, test), and listing of projects/tools. Missing delete/update for orchestrations and projects, but those may be out of scope. Minor gaps, but core workflows are complete.