SHIP MCP server
Assign Linear, Jira or GitHub issues to an AI coding agent team. Its coding agents plan and build each change, run code review and tests, and open a pull request in your GitHub repository. With this MCP server, your assistant can file missions, follow them, send instructions and read the proof of each run.
SHIP runs an agentic SDLC as a headless AI software factory. You operate the whole mission from your coding agent or AI assistant. Start it, send instructions, read its code review and test reports, and approve the pull request. A Planner, a Builder, a Reviewer and a Tester each do one stage, and your CI is a gate between them. Each role runs the coding agent and the model that you choose: Claude Code, Codex, OpenCode, Kilo Code or the pi coding agent.
Endpoint
https://mcp.letsship.ai/mcp
The transport is Streamable HTTP. The server is stateless, so a client can reconnect at any time and lose nothing.
Sign in
OAuth 2.1. A client that supports MCP authorization finds the sign-in automatically. If a request needs a token and has no valid token, the server answers 401 with a WWW-Authenticate header.
The header points to https://mcp.letsship.ai/.well-known/oauth-protected-resource/mcp. SHIP supports dynamic client registration and client ID metadata documents, so you do not have to register a client first. You approve the sign-in in the SHIP console.
Personal access token. A client without OAuth sends Authorization: Bearer pat_.... Create a token at https://letsship.ai/settings/tokens. Bind it to one project, so that it can reach only that project.
Install
Claude Code
claude mcp add --transport http ship https://mcp.letsship.ai/mcp
Claude and ChatGPT. Add a custom connector with the URL https://mcp.letsship.ai/mcp. Sign in when the app asks.
Cursor. Use the button above, or add this to .cursor/mcp.json:
{
"mcpServers": {
"ship": {
"url": "https://mcp.letsship.ai/mcp"
}
}
}
VS Code. Use the buttons above, or add this to .vscode/mcp.json:
{
"servers": {
"ship": {
"type": "http",
"url": "https://mcp.letsship.ai/mcp"
}
}
}
Codex. Add this to ~/.codex/config.toml:
[mcp_servers.ship]
url = "https://mcp.letsship.ai/mcp"
Grok. Open grok.com/connectors. Select New Connector, then Custom. Paste the URL https://mcp.letsship.ai/mcp. Then sign in.
xAI API. Pass the URL as a remote MCP tool, with a token in headers:
{
"type": "mcp",
"server_url": "https://mcp.letsship.ai/mcp",
"server_label": "ship",
"headers": {
"Authorization": "Bearer pat_your_token_here"
}
}
A client that supports only stdio connects through mcp-remote:
{
"mcpServers": {
"ship": {
"command": "npx",
"args": [
"-y",
"mcp-remote",
"https://mcp.letsship.ai/mcp"
]
}
}
}
With a token. Add the header to any of the HTTP entries above:
{
"mcpServers": {
"ship": {
"url": "https://mcp.letsship.ai/mcp",
"headers": {
"Authorization": "Bearer pat_your_token_here"
}
}
}
}
Tools
Each tool declares readOnlyHint, destructiveHint and openWorldHint. With these hints, your client can run a read-only tool immediately. It can also ask you before it runs a tool that removes or replaces something, or opens a payment page. The scopes of the token decide what each tool can do, and a refusal names the scope that the token does not have.
[!IMPORTANT]
start_mission,create_missionandrun_scheduled_taskstart a mission, and each mission start costs one credit. Messages to an active mission are free.
Missions
Projects and proof
Scheduled tasks
MCP servers for your agents
Agent runs
Preview environments
Credits and notices
Custom sandboxes
Platform operators
Identity
Example: file a fix and answer the review
- Call
list_projectsto get the project id. - Call
create_missionto file the issue and start the mission. Write the acceptance criteria as checkboxes, because the Tester uses them to test the work. - The agents plan the change, build it and open a pull request. Then they wait for your CI, review the change, deploy a preview and test it. This takes tens of minutes, and your assistant does not have to wait.
- Call
inspect_missionto read the stage and the verdicts. To disagree with a review, callsend_mission_instructionwithkind: "follow_up". The Builder then works on the pull request again and follows your instruction.
To send feedback, use send_mission_instruction. Do not call start_mission again, because a restart does not take a message.
Troubleshooting
Skills for your coding agent
The SHIP skills teach a coding agent to hand work to SHIP from the terminal. To install them, see letsship/skills or run npx skills add https://letsship.ai.
Learn more
- What an agentic SDLC is, from issue to verified pull request
- What an AI software factory is, and how to build one
- SWE-in-a-team, a coding agent benchmark of 260 missions
- Run the pi coding agent headless
- Send a pull request that your coding agent wrote for review and test
Links
- Docs: https://letsship.ai/docs/mcp
- Registry entry:
ai.letsship/shipon https://registry.modelcontextprotocol.io - A2A agent: https://letsship.ai/docs/a2a
- Privacy: https://letsship.ai/privacy - Terms: https://letsship.ai/terms
- Support: https://letsship.ai/support
- Security reports: support [at] letsship.ai
License
The files in this repository are under the MIT license. The SHIP service is under the SHIP terms.