Skip to main content
Glama
Otha-Labs

Persuasion Taxonomy MCP

Find persuasion techniques

find_persuasion_techniques
Read-onlyIdempotent

Search 766 named persuasion techniques from real ads by describing what your copy should do—build trust without testimonials or create urgency without fake scarcity—and get matching tactics.

Instructions

Search the Persuasion Taxonomy, 766 named persuasion techniques documented from real advertising and organized by the nine reader questions they answer. Describe what you want the copy to do, like build trust without testimonials, create urgency without fake scarcity, handle a price objection, make an opening less generic, prove a claim or reframe a problem. It finds the techniques that do it. Each one comes with its name and ID, a one-line definition, a real example, how common it is in a category if you name one, and a link. So reach for it when a draft relies on the obvious move and you want a less expected one, or when someone asks for tactics, angles, hooks or ideas.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYesWhat you want the copy to do, in plain words, like "prove it works without testimonials".
formatNoThe kind of copy it is: ad, landing_page, sales_letter for long-form sales copy, email, email_subject, social_post, video_script or headline.
categoryNoThe industry, if you want to compare against what brands in that category usually do. There is enough data for apparel, automotive, b2b_saas, beauty_skincare, business_coaching, consumer_tech, dtc_food_bev, dtc_health, fitness_health, home_goods, info_product, investing, marketing_education, otc_pharma, personal_care, personal_development, supplements, weight_loss. Any other category still works, just without the comparison.
questionNoSet this to see only the techniques that answer one reader question.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent and closed-world, so the safety profile is covered. The description adds genuinely useful behavior beyond that: the exact contents of each result (name and ID, one-line definition, real example, category frequency if a category is named, link), which matters because there is no output schema.

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

Conciseness4/5

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

Front-loaded with the corpus definition, then usage scenarios, in a logical order. Slightly loose — 'It finds the techniques that do it.' is filler and the long run-on sentence mixes four separate example queries that partly duplicate the schema's own query example.

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

Completeness4/5

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

With no output schema, the description usefully specifies what comes back, and it covers corpus size, organization and triggering scenarios. Minor gaps: nothing about result ordering/relevance or how the default limit of 8 affects behavior, though the schema covers those parameters.

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 description coverage is already 80%, so the baseline is 3. The description earns above baseline by explaining intent-level semantics: the query is phrased as 'describe what you want the copy to do' with multiple worked examples, and it clarifies that any category value other than the listed ones still works but suppresses the comparison signal.

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?

States a specific verb and resource — search the Persuasion Taxonomy of 766 named techniques organized by nine reader questions — and makes the scope concrete enough to separate it from the singular get_persuasion_technique sibling. An agent can tell what it returns and roughly how the corpus is structured without opening the schema.

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

Usage Guidelines4/5

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

Gives explicit triggering contexts: 'reach for it when a draft relies on the obvious move and you want a less expected one, or when someone asks for tactics, angles, hooks or ideas.' Strong when-to-use signal, but it never names an alternative tool or states when not to use it (e.g. the single-technique lookup or the diagnostic siblings).

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