Categories › AI & Agents › Multi-agent, orchestration & workflows
Turn an idea or meeting transcript into a working single-file AI agent, check it, use it right away.
Remote server: your requests and data go to api.airaptr.com. Claude Code: claude mcp add --transport http raptr-agent-builder https://api.airaptr.com/mcp · Claude app: Settings → Connectors → Add custom connector.
The tools this server listed when we connected to it, in its own words.
get_agent_template — Use this when the user wants to build an AI agent, assistant, bot or automation from an idea, a repetitive task, a process description, or acheck_agent — Checks a finished agent file against the template rules (manifest, naming, class, perform method, no hardcoded secrets). Call it on every agfind_agents — Searches the open agent registry (about 1,700 single-file agents) for agents that already do what the user wants, for example when they ask get_agent_code — Returns the full source of one agent from the registry, by its name (e.g. @bill/neuron_agent), so it can be read or adapted.use_agent_here — Use this right after an agent passes check_agent, or whenever the user wants to try an agent. Returns a short Python runner so you can run thow_to_run_agent — Optional, for later: how to keep an agent running on the user's own computer with the free Brainstem. Only offer this after the user has useshare_agent — Use only when the user says they want to share an agent they built. Checks the agent and scans it for personal details (emails, phone numberrejection_rescue_preview — Use when the user pastes a rejection message from Apple App Review (it cites guidelines such as "Guideline 5.1.1(i)"). Free. Returns each cirequest_service — Use when the person wants something none of these tools can do and says yes to passing the request on. Records only the request text they agNot tested by KitScout yet. When our harness runs it, pros, cons and the tasks we tried appear here, with the date and evidence.