Sandbox login
Authenticate once with tenant-scoped credentials before running guardrail, MCP, or diagnostics commands.
Paybond CLI
Paybond CLI is a terminal tool for setting up guardrails, MCP configuration, diagnostics, and JSON automation for agent spend workflows. It supports both TypeScript and Python with the same command tree and output contract.
Safe agent spend from the terminal
Paybond CLI is a terminal-first tool for setting up safe agent spend with Paybond Kit. It combines sandbox login, guardrail scaffolding, MCP configuration, diagnostics, and automation in one command surface for both TypeScript and Python runtimes.
The CLI is designed for workflows that need spend controls before a coding agent uses a paid tool. The documentation shows a sandbox-first setup flow, then MCP installation and validation, with JSON output available for scripting and CI.
Core capabilities
Guardrail scaffolding
Create a first paid-tool guardrail from a preset that matches the framework and output path, with separate paths for TypeScript and Python.
MCP setup and verification
Install and verify MCP host configuration, including the env-file pattern used by coding agents.
Doctor and diagnostics
Check credentials, principal lookup, MCP startup, and tool listing before agents hit production spend paths.
JSON automation
Return stable JSON envelopes for scripts, CI pipelines, and agent automation.
Runtime parity
Keep the command tree, help text, and exit codes aligned across the TypeScript and Python kits.
Common workflows
Bootstrapping a first agent integration
Use the CLI to log into a sandbox tenant, scaffold a first paid-tool guardrail, and validate that the agent path is wired correctly before any live spend is involved.
Configuring an agent host
Install MCP host configuration for a coding agent, using the same environment-file pattern that the docs recommend for local setup and verification.
Preflight checks before production
Run doctor checks and diagnostics to catch credential issues, principal lookup problems, or MCP drift before a workflow reaches production spend paths.
Automating agent setup in CI
Use the JSON output mode in scripts or CI when a workflow needs stable machine-readable envelopes instead of terminal-only output.
Using one runtime consistently
Choose either the TypeScript or Python kit when a team already has a preferred runtime but needs the same command tree and CLI contract.
Pros and Cons
Pros
- One shared command tree for TypeScript and Python.
- Supports sandbox login, guardrail scaffolding, MCP setup, diagnostics, and JSON automation.
- Built around tenant-scoped credentials and masked terminal output.
- Has a documented setup path for coding agents that includes MCP validation.
Cons
- The source emphasizes sandbox-first setup and separates production spend flows into later lifecycle steps.
- Some command behavior is documented in the CLI contract rather than on the product page, so the public overview is partial.
FAQ
Do I need both TypeScript and Python?
No. The source says both the TypeScript and Python kits expose the same `paybond` command tree and JSON contract, so you can pick the runtime your agent or app already uses.
Can the CLI return machine-readable output?
Yes. The CLI supports `--format json` with stable envelopes for scripts, CI, and agent automation.
How does the CLI relate to the MCP server?
The CLI installs and verifies MCP host configuration, while the MCP server itself is launched separately through `npx` or the host's stdio config after login.
What is the basic setup flow for a coding agent?
The documented sandbox path is `login`, scaffold a guardrail, install MCP config, then run `doctor --agent` to validate credentials, principal lookup, MCP startup, and tool listing.
Is this only for sandbox use?
The source distinguishes sandbox-only flows from production flows. The first guardrail and login path are for sandbox use, while live settlement rails and production spend flows belong on higher tiers and the later production lifecycle.
Quick Facts
- Category
- Developer Tool
- Primary use
- Safe agent spend setup from the terminal
- Platforms
- TypeScript and Python
- Output mode
- Table and JSON
- Source domain
- paybond.ai
- Related workflow
- MCP setup and diagnostics
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