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create_account

Create an account-bootstrap session for agent-driven onboarding, returning a session ID and channel-specific instructions, including a QR code for Telegram/WhatsApp or SMS message to send.

Instructions

Create an account-bootstrap session for agent-driven onboarding. Public endpoint (no API key required). Returns a session id, channel-specific instructions, and — FOR TELEGRAM AND WHATSAPP ONLY — deep_link, qr_code (base64 PNG) and qr_text (UTF-8 text QR).

The endpoint is safe to call regardless of whether the submitted identity is new: completing verification transparently creates a User when none exists, or logs the user in when one already does. The response is intentionally uniform — the server does NOT reveal whether the identity is already registered (this would be a user-enumeration oracle). If the agent needs to distinguish new-vs-returning users, call get_current_user after verification and inspect the user's created_at.

EMAIL CHANNEL SENDS NOTHING HERE. The response carries email_sent=false and send_required=true: confirm with the user that the address is theirs, then call send_account_email. The other channels dispatch nothing either way — the user sends the first message themselves (reverse OTP).

Agent usage: (1) Call create_account with the user's chosen channel. (2) For email, confirm with the user and call send_account_email. On telegram/whatsapp pass deep_link to render_auth_link, which prints the clickable link and a QR code beneath it. On sms deep_link is an EMPTY STRING and render_auth_link will reject it — show sms_message, which is what the user sends; this response carries no destination number, so do not invent one. Do not hand qr_text to a link renderer either — it is the link already rendered as QR art; print it verbatim inside a fenced code block if a real terminal needs the QR. (3) Call wait_for_account_creation with the session id until verification completes. (4) On verified, JWT + refresh cookies are set; proceed with whatever follow-up the agent was asked to do.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailNoEmail address. Required for email channel.
channelYesAuthentication channel the user will verify through
phone_numberNoE.164 phone number. Required for SMS channel (determines DID routing).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.1.0

TDQS

A4.6/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description fully carries the behavioral disclosure burden. It reveals that the endpoint is public, that it creates a user or logs one in, that the response is intentionally uniform to avoid user enumeration, that email sends nothing, that sms responses contain no destination number, and that verification sets JWT and refresh cookies. This is exceptionally transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Although lengthy, the description is dense, well-structured, and front-loaded with the core purpose before the workflow. Every paragraph and numbered step earns its place given the channel-specific caveats, and the warnings are concrete rather than generic.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description takes on the burden of explaining return fields and follow-up expectations. It covers session id, deep_link, qr_code, qr_text, sms_message, email_sent, send_required, and the verification handoff. It also covers edge cases like sms lacking a destination number and the danger of treating qr_text as a link. This is complete for an onboarding tool with this complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already covers all three parameters with 100% coverage, so the baseline is 3. The description adds meaningful channel-specific semantics: email requires confirmation and a follow-up call, sms requires a phone number with no destination in the response, and telegram/whatsapp use deep_link for rendering. It does not fully enumerate parameter formats beyond the schema, but it substantially augments the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description identifies a specific verb and resource ('Create an account-bootstrap session for agent-driven onboarding') and adds the public-endpoint qualifier. It is clear, but it does not explicitly differentiate itself from closely related siblings like create_session, start_login, or create_verification, so an agent must infer the distinction from context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives an explicit numbered agent workflow, including when to call send_account_email versus relying on deep_link, when to use render_auth_link, and when to call wait_for_account_creation. It also states the condition for calling get_current_user to distinguish new vs. returning users, and warns against using sms deep_link or handing qr_text to a link renderer.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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