Use with AI agents

AI agents can do in your workspace what you could do yourself — within the access you give them, as you, and recorded in the audit log. Three ways, from the least setup:

Your agent	Use
Claude, ChatGPT or another MCP-capable app	the MCP server — nothing to install
A coding agent with a terminal	the command line, with --json
Your own software	the API or SDK

MCP server

Add https://mcp.limitry.com/mcp as a remote MCP server in your agent. You sign in once in the browser, choose one workspace and what the agent may do; its tools are exactly that. Details and safeguards: MCP server.

Command line

Coding agents (Claude Code, Cursor, Codex …) work well with the command line:

npm install -g @limitry/cli
limitry login                                  # you approve it in the browser
limitry workspace list --json
limitry workspace webhook-endpoints list --workspace acme --json

--json gives the agent the API’s exact JSON, errors as JSON on stderr, and a 0/1 exit code. In CI or a sandbox without a browser, set LIMITRY_TOKEN to a personal access token limited to what the agent needs.

Teach your agent: the skill

The agent skill is one file that teaches an agent everything above — how to sign in, choose the workspace, every command and tool, the error codes, and what to leave to a person: /docs/skill/SKILL.md. It is generated from the API, so it always matches.

For Claude Code, install it for every project:

mkdir -p ~/.claude/skills/limitry
curl -fsSL https://limitry.com/docs/skill/SKILL.md \
  -o ~/.claude/skills/limitry/SKILL.md

(or into a project’s .claude/skills/limitry/). Other skills-aware agents take the same file in their own skills folder.

Docs for agents

The documentation is available as plain text for agents: /docs/llms.txt (an index of every page) and /docs/llms-full.txt (everything in one file). The site’s /llms.txt indexes these, the API, the MCP server and the skill.

What agents cannot do

Some operations stay with people even when an agent has full access — anything that sends your workspace’s data somewhere new or hands out access (for example, creating API keys or adding webhook endpoints). An agent asks instead, and you approve or deny — see Approvals; a secret it creates never reaches the agent.