Coppica MCP server

• Registry namecom.coppica/persuasion-taxonomyverified in the MCP registry

The registry name sits under coppica.com. The registry only lets a publisher use that namespace after proving control of the domain through DNS or HTTP.

• Stateanswerschecked 2026-10-20
• Tools9
• Server calls itselfpersuasion-taxonomy
• Server version1.0.3
• Protocol version2025-06-18

On 2026-10-20 the server answered initialize and tools/list without a sign-in. First answer in 151 ms.

• Its tools do none of the product's use cases we checked: Search past ads and emails by persuasion technique; Draft new ads, emails and landing pages from past winners.
• Checked on 5 of the 7 days it takes to judge reliability.

Said by rules from the measurements above. The likely first call is a model's pick from the tool list; read its description before relying on it.

• INITE MCP scoreafter a weeka score needs 7 daily checks: 5 so far
• What an agent can do with it0 of 2 use cases
• Use30 npm downloads a week1 GitHub stars
• Answeredmeasuring5 of the 7 daily checks it takes to print a share
• Median first answer132 ms
• Space in an agent's context≈ 6,054 tokensthe definitions of all its tools (9), which an agent carries on every turn
• Tool definitionsA · 91 of 100
• Typed results0 of 9 toolsdeclared outputSchema: results come typed, read once

• Parameters without a description: in 5 of 9

A program checks the server once a day: initialize and tools/list, no model. Tokens are the definitions' length at about four characters a token. The grade averages six checks of every tool's name, description, schema and annotations; it says how well the tools are described, not whether they work. The score weighs what was measured and nothing else: answering (30%), doing the product's job (25%), definitions (20%), context (10%) and use (15%). A part that was not measured is left out, and a hidden instruction caps the score at 40. The state of vendors' MCP servers: method and numbers →

• plan_marketing_copy

  Plan any piece of marketing copy before you write it, whether it's an ad, a landing page, a sales page or sales letter, an email, a subject line, a social post, a headline or a video script. Give it the goal, the reader and the offer, and…

• diagnose_marketing_copy

  Review, critique or roast any piece of marketing copy, whether it's an ad, a landing page, an email, a sales page, a social post or a script, and find out why it might not persuade. Before you call it, read the copy and label each line…

• explain_why_not_converting

  Work out why an ad, a landing page, an email or a whole funnel isn't converting. Start from what you can see. Maybe people don't click (a low CTR), or they click and bounce, or they read and don't buy. Maybe they abandon the checkout or…

• find_persuasion_techniques

  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…

• get_persuasion_technique

  Look up one persuasion technique by its ID (like PT-PRV-10000), its slug or its name. You get the full definition, why it works, when it lands and when it backfires, real examples from advertising, related and opposite techniques, and a…

• check_headlines

  Check headlines, email subject lines, ad openings, video hooks, social post openings and first lines, and compare options against each other. For each line it tells you whether the line does its job in that spot, meaning which of the nine…

• check_marketing_claims

  Check whether marketing claims and calls to action are specific enough to believe. It catches the vague superlative, like "the best" or "#1", that readers discount on sight. It catches promises with no proof behind them and results with…

• plan_ab_test

  Plan an A/B test for marketing copy. Give it the current conversion rate, the smallest lift worth detecting and the daily traffic, and it tells you how many visitors each version needs and how many days to run. It also frames the test as…

• read_ab_test_result

  Read the result of an A/B test. You get each version's conversion rate and lift, whether the difference is statistically significant, the confidence interval, and the chance each version really beats the original. It also warns you about…