parapetai-mcp
MCP server for Claude Code (and other MCP clients) that talks to a Parapet control plane: device-code login in your browser, then provision governed agents and pull the exact quickstart config a codebase needs — without hand-editing env vars.
pipx install parapetai-mcp
parapetai-mcp init # installs SKILL.md into .claude/skills/parapet/
claude mcp add parapet -e PARAPETAI_CONTROL_PLANE_URL=https://app.parapet.run -- parapetai-mcp serve
pipx, not pip — this is a CLI tool (a [project.scripts] entry point), not a
library anything imports, and most Python installs on macOS/Linux now ship as
PEP 668 "externally managed" (Homebrew's Python does), which makes a bare
pip install parapetai-mcp fail rather than risk corrupting packages the
system relies on. pipx installs CLI tools into their own isolated venv and
puts the entry point on PATH — no venv to activate, no --break-system-packages
flag needed. No pipx available? python3 -m pip install --user pipx && pipx ensurepath (or brew install pipx on macOS), then re-run the command
above. uv tool install parapetai-mcp is an equivalent one-liner if uv is
already on the machine.
Then in Claude Code: "add Parapet to this project."
Tools
| Tool | What it does |
|---|---|
parapet_login |
Device-code login — open the printed URL, approve in your browser |
parapet_whoami |
Who you're authenticated as, and which agents already exist |
parapet_provision_agent |
Provision a new governed agent (agent_id + one-time secret) |
parapet_get_quickstart |
The install command / env var names this deployment expects |
parapet_list_agents |
Read-only agent listing |
This server never edits your project's files — it only talks to the
control plane. The packaged SKILL.md tells Claude Code how to use these
tools and where to write the resulting config.
Point at a different control plane (e.g. a local make dev instance) with
PARAPETAI_CONTROL_PLANE_URL (default https://app.parapet.run, the hosted
control plane).
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