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Glama

Storyflo

by io.github.Alisammour

Get embedder onboarding URL

register_embedder
Read-onlyIdempotent

Resolve the storyflo embedder onboarding URL prefilled with the partner's name + email + optional vertical. Returns the URL the human must visit to complete signup (storyflo emails a magic link to verify ownership; the embedder slug + ref_token are minted on verification). DOES NOT create a DB row + DOES NOT send email — the MCP tool is a discovery + handoff surface so an agent can call it speculatively without triggering inbox-bound email to the human. Public — no auth required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesDisplay name for the embedder (publisher / agent product).
emailYesContact email — must contain '@'. Storyflo emails the magic link here on signup.
verticalNoOptional vertical scope (tech / finance / news / etc.).

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the annotations (readOnly, idempotent, non-destructive), the description discloses key behaviors: it returns a human-visited URL, the magic link flow, verification triggers slug/ref_token minting, and it never sends email or creates rows. This adds significant behavioral context.

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?

The description is dense and front-loaded, with every sentence adding critical information: the URL resolution, the no-side-effect guarantee, and the public access. No wasted words.

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?

For a tool with three params, no output schema, and strong annotations, the description fully covers the return value, side effects, auth, and use case. It is complete for an agent to decide on and invoke the tool correctly.

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?

Schema coverage is 100%, but the description reinforces how parameters are used (prefilled into the URL) and explains the email magic-link flow. It adds a bit of semantic meaning beyond the schema descriptions, though not much new.

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

Purpose5/5

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

The description clearly states the tool's purpose: resolving the storyflo embedder onboarding URL prefilled with partner's name, email, and optional vertical. It distinguishes itself from siblings like get_embedder_manifest by focusing on the onboarding URL handoff, not manifest retrieval.

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 provides explicit usage guidance: it is a discovery + handoff surface for speculative calling, and it explicitly states what the tool does NOT do (no DB row, no email sending, public/no auth). This tells the agent when to use it and when not to expect side effects.

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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TDQS

A3.8/5.0
Disambiguation5/5

Every tool has a clearly distinct purpose, with detailed descriptions that prevent ambiguity. Even similar tools like search_articles, search_declassified, and search_unified target different corpora, and the publisher tools are well-separated. No overlap that would confuse an agent.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with snake_case, using clear prefixes like get_, search_, subscribe_, publisher_, fm_, digest_, etc. The naming is predictable and systematic, making it easy for an agent to infer functionality.

Tool Count4/5

At 37 tools, the count is higher than the typical 3-15 range for a coherent set, but the server covers a wide domain (content retrieval, podcast management, fund manager book, embedder network, etc.). Each tool earns its place, though the set could be slightly reduced by merging some rare-use tools.

Completeness4/5

The tool surface is comprehensive for the server's purpose—search, audio, subscriptions, publisher workflows, and special features like the Divergence Index. Minor gaps exist (e.g., no explicit unsubscribe tool, no article update/delete), but they are not critical for core workflows.

Resources