Octopilot
БесплатноНе проверенModel Context Protocol (MCP) server for Octopilot — enables AI agents to detect, generate, build, and wire up new repositories end-to-end using the Octopilot CI
Описание
Model Context Protocol (MCP) server for Octopilot — enables AI agents to detect, generate, build, and wire up new repositories end-to-end using the Octopilot CI/CD toolchain.
README
Model Context Protocol (MCP) server for Octopilot — enables AI agents to detect, generate, build, and wire up new repositories end-to-end using the Octopilot CI/CD toolchain.
What it does
| Tool | Description |
|---|---|
detect_project_contexts |
Parse skaffold.yaml → pipeline-context JSON (languages, versions, matrix) |
generate_skaffold_yaml |
Generate a skaffold.yaml for given artifacts |
generate_ci_workflow |
Full .github/workflows/ci.yml using the standard octopilot pipeline |
onboard_repository |
One-call onboarding: detect → generate files → return next steps |
run_op_build |
Run op build via local binary or ghcr.io/octopilot/op container |
list_actions |
All Octopilot GitHub Actions from the bundled registry |
get_action_details |
Full spec, inputs, examples, gotchas for one action |
op promote-imageis intentionally not exposed. Image promotion between environments is operationally sensitive and must only run through a GitHub Actions workflow (with audit trail, OIDC credentials, and environment protection rules). Usegenerate_ci_workflowto produce the workflow that handles promotion safely.
Option A — Hosted (zero install)
Connect directly to the public server at https://mcp.octopilot.app — no cloning, no Python, no pip required.
# Cursor
fastmcp install cursor https://mcp.octopilot.app --name octopilot
# Claude Desktop
fastmcp install claude https://mcp.octopilot.app --name octopilot
Available hosted tools (stateless, no local dependencies):
| Tool | Description |
|---|---|
list_actions |
Browse the Octopilot GitHub Actions registry |
get_action_details |
Full spec, inputs, examples, gotchas for one action |
generate_skaffold_yaml |
Generate a skaffold.yaml for given artifacts |
generate_ci_workflow |
Full .github/workflows/ci.yml for a project |
Need
detect_project_contexts,onboard_repository, orrun_op_build? Those tools need Docker and local filesystem access — use Option B below.
Option B — Local install (full suite)
# Clone and install
git clone https://github.com/octopilot/octopilot-mcp
cd octopilot-mcp
uv sync
Usage
Register with your IDE (one command, FastMCP 3 CLI)
Docker or Colima is the only external dependency. Most tools are pure Python;
run_op_build pulls ghcr.io/octopilot/op:latest automatically with
--pull always, so you always run the latest release.
# Cursor
uv run fastmcp install cursor src/octopilot_mcp/server.py --name octopilot
# Claude Desktop
uv run fastmcp install claude src/octopilot_mcp/server.py --name octopilot
Development (hot-reload)
uv run fastmcp dev src/octopilot_mcp/server.py --reload
Inspect tools from the terminal
# List all available tools
uv run fastmcp list src/octopilot_mcp/server.py
# Call a tool directly
uv run fastmcp call src/octopilot_mcp/server.py tool_list_actions
Run as a server directly
uv run octopilot-mcp
Manual JSON config (alternative to fastmcp install)
{
"mcpServers": {
"octopilot": {
"command": "uv",
"args": ["run", "--directory", "/path/to/octopilot-mcp", "octopilot-mcp"]
}
}
}
Pin to a specific op release (optional):
{
"mcpServers": {
"octopilot": {
"command": "uv",
"args": ["run", "--directory", "/path/to/octopilot-mcp", "octopilot-mcp"],
"env": { "OP_IMAGE": "ghcr.io/octopilot/op:v1.0.0" }
}
}
}
Environment variables
| Variable | Default | Description |
|---|---|---|
OP_IMAGE |
ghcr.io/octopilot/op:latest |
Pin to a specific op release for reproducibility |
Example agent interaction
User: Onboard this Rust API project to use Octopilot CI.
Agent: [calls onboard_repository("/path/to/my-api", "ghcr.io/my-org")]
→ Detected: rust (stable) in api/
→ Generated: skaffold.yaml, .github/workflows/ci.yml
→ Next steps: add .pre-commit-config.yaml, push changes
Development
uv sync --all-extras
# Run tests
uv run pytest tests/ -v
# Run with coverage
uv run pytest tests/ --cov=src/octopilot_mcp --cov-report=term-missing
Tool module coverage target: ≥95% (actions, detect, generate, op_runner).
See CONTRIBUTING.md for details.
Resources
The server also exposes MCP resources for agent context:
octopilot://actions— Full actions registry JSONoctopilot://pipeline-context-schema— JSON Schema for pipeline-contextoctopilot://docs/getting-started— Plain-text onboarding guideoctopilot://docs/skaffold-patterns— Commonskaffold.yamlpatterns
Установка Octopilot
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/octopilot/octopilot-mcpFAQ
Octopilot MCP бесплатный?
Да, Octopilot MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Octopilot?
Нет, Octopilot работает без API-ключей и переменных окружения.
Octopilot — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить Octopilot в Claude Desktop, Claude Code или Cursor?
Открой Octopilot на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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