Dali by Lulu MCP server

• analyze_intentFree

  Parse a creative prompt into structured intent dimensions.

• analyze_winning_formulaFree

  Find YOUR winning ad formula from your own numbers — paste your ads export. The category prior is a cold-start fallback; the real signal is what wins in YOUR account. Paste an ads CSV (a creative image-URL column + a performance column — CPA / CTR / ROAS / purchases) and Dali runs vision on your winners vs losers and returns the attributes that separate them, plus how your account compares to the industry median. If an email is supplied, the formula is saved and emailed with a ready-to-paste Claude prompt wired to Dali — so scoring the next creative is one step. Returns: formula — attributes over-represented in your winners (value, winner%/loser%, lift) benchmark — your median vs the vertical's industry median (when category given) analyzed — how many winners/losers were read, and the metric direction saved — whether the lead+formula were captured (only when email supplied)

• community_benchmarkFree

  Compare your prompt against community top scorers for this generator. Returns your score, missing A-grade patterns, and highest-ROI patterns to add.

• creative_patternsFree

  Community graph: which patterns consistently produce high-grade prompts for this generator? Powered by the V3 graph brain (Supabase PostgreSQL). Every scored prompt contributes. Returns top patterns by type, enhancement unlocks, and cross-model universal patterns.

• dali_versionFree

  Current Dali MCP version and changelog. Check this whenever you want to know what tools are available, what changed in the latest release, or which version is running.

• enhance_promptFree

  Get a rewrite brief for this prompt + generator. YOU write the enhanced prompt from the brief. Returns a structured brief with score_before, rewrite_brief, and llm_instructions. category (optional): the ad vertical (e.g. "wellness", "beauty") if known. When set and conversion priors exist for it, the brief upgrades from craft advice to a conversion-justified one, backed by real ad-performance data. IMPORTANT: After you write the enhanced prompt, you MUST call track_enhancement(original_prompt, your_enhanced_prompt, generator) immediately. This is not optional — it records the improvement and is required for the graph to learn.

• enhancement_pathFree

  Show the most reliable path from a bad grade to an A on this generator. Mines the Dali graph for all F/D → A/B enhancement pairs and surfaces the patterns that appear most consistently in the 'after' side. These are the highest-ROI moves for this specific generator. Use this when: - A prompt just scored D or F and you're not sure what to fix - You want to know which improvements matter most for a specific generator - You want to understand generator-specific enhancement strategy

• list_generatorsFree

  List all supported generation targets (providers + models) with medium and core strength.

• my_storyFree

  Your Dali creative report — scoring history, generator stats, recent scorers, creative DNA.

• prompt_neighborsFree

  Find community A/B-grade prompts structurally similar to yours. Uses graph traversal (Memgraph) to locate prompts that share the most creative patterns with your input and scored A or B on the same generator. Returns what those prompts did right — so you can adopt the same moves. Use this when: - Your prompt scored C or below and you want inspiration - You want to see how the community solved the same creative problem - You need concrete A-grade examples, not abstract advice

• score_creativeFree

  Score an actual ad IMAGE (not the text prompt) for conversion — before you spend. Conversion lives in the pixels, so this scores the real creative and gives you ONE answer combining two views, in a single call: • HEADLINE score = how much it visually resembles PROVEN WINNERS (Vertex embedding vs the live winner corpus). The sharpest predictor — it reads the whole look and self-solves archetype (a premium ad resembles premium winners, not scammy direct-response ones). • WHAT TO CHANGE = the specific winning attributes it's missing (Gemini vision vs category priors) — the actionable detail. • DEFECT GATE = generation defects (extra fingers, garbled text, warped anatomy). Use it on a generated image, a mockup, or any ad you're about to run. Returns: score — 0-100 headline: visual similarity to proven winners verdict — one-line looks-like-a-winner / partial / rework call looks_like — the real proven winners it resembles (advertiser, category, days-run) what_to_change — high-lift winning attributes it lacks, each with a fix sentence you_already_have — winning attributes it already has has_defect/defects — generation defects to fix before shipping detail — raw numbers {embedding_score, attribute_score} for transparency category examples: beauty, supplements, wellness, fitness, food, apparel, tech, pets. Leave category empty for a cross-vertical look-alike match + defect QA.

• score_creative_from_viewFree

  Score an ad creative YOU are looking at (e.g. a pasted/attached image) against the winning corpus — no URL needed. Use this when the user shares an image in the conversation: read the creative yourself and fill in what you see, and Dali scores it against what wins in the category (3,800+ proven winners), returning the conversion verdict and exactly which winning attributes it's missing. You (the model) provide the visual read; Dali provides the winning-data scoring. (For a fetchable image URL, prefer score_creative — it adds the embedding similarity headline, which needs the real pixels.) Fill these from looking at the image: category — vertical: beauty, wellness, supplements, fitness, food, apparel, tech, pets lighting — warm lighting | natural light | studio light | dramatic lighting | clinical bright | dark moody | neon subject — single person | group | product only | no person | before after subject_age — young adult | middle age | senior | child | none format — ugc selfie | testimonial | product hero | lifestyle | chart infographic | text meme | comparison text_density — none | light | heavy dominant_emotion — calm | excited | trust | fear | aspiration | neutral eye_contact — true if a person looks at camera offer_visible — true if a price/discount/offer is shown defects — list any generation defects (extra fingers, garbled text, warped anatomy); [] if clean Returns: conversion_score (0-100), verdict, matched (winning attributes it has), missing (high-lift attributes to add, each with a fix sentence), has_defect/defects.

• score_promptFree

  Score a prompt for a generation target (0–100) and, if it's weak, return the rewrite brief — in ONE call. Reads intent with a fast heuristic keyword analyzer, scores the prompt, then: • score ≥ 70 (A/B) → returns the scorecard and tells you to proceed. • score < 70 (C/D/F) → returns the scorecard PLUS a rewrite brief so you can fix it without a second call. Write the enhanced prompt from the brief, then call track_enhancement(original, enhanced, generator). Returns a ScoreCard (overall, grade A–F, per-dimension breakdown, what's missing, anti-patterns, verdict) plus needs_enhancement, and enhancement_brief when weak. category (optional): the ad vertical (e.g. "wellness", "beauty") — when set and conversion priors exist, the brief upgrades to a conversion-justified rewrite. Supported generators: veo3, higgsfield, midjourney, flux, kling, sora, imagen…

• score_variationsFree

  Score 2–8 prompt variations for the same generator and rank them best-to-worst. Use this when you've drafted multiple versions of a prompt and want to pick the winner without burning generation credits. Returns a ranked list with per-dimension comparison so you can see exactly why one variant beats another.

• suggest_generatorFree

  Recommend the best generator for your creative concept and per-generation budget. Analyzes the concept's creative signals (motion, style, subject type, use case) and matches them to generators within your budget. Returns a ranked list so you can make an informed choice before scoring the actual prompt.

• track_enhancementFree

  Record an enhancement pair in the Dali graph brain. Call this AFTER you write an enhanced prompt from score_prompt's brief or enhance_prompt. This records the before→after improvement so the graph learns which rewrites consistently push scores up — enriching creative_patterns and community_benchmark over time. Returns before/after scores so you can confirm the delta.

• Code scan10 source files scanned20/25
• Live reliabilityremote unreachable: AbortError: This operation was aborted0/20
• –Tool poisoningtools not inspected (endpoint requires auth); not countedn/a
• Auth qualitylocal package, no credentials required12/15
• Maintenancelast push 104 days ago8/15
• Maintainer identityregistry namespace matches repository owner6/10

Safety score

54/100

higher than 13% of 4,456 AI and agents servers

Tools

16

the typical AI and agents server has 7

Tools that change things

0%

typical: 3%. Fewer write tools means less an agent can break

Uptime

0%

of our recent checks; the typical remote AI and agents server answers 100%

Response time

216 ms

faster than 57% of 2,337 AI and agents servers

GitHub stars

9

more than 83% of 2,733 AI and agents servers

Downloads a week

41

more than 20% of 1,712 AI and agents servers with a package

Grade history

• 2026-10-25downgradeB → Dscore 54: Remote endpoint did not respond; Network call to a raw IP address

Dali by Lulu: common questions

Is Dali by Lulu MCP server safe?

Not recommended: it is graded D (54/100). Read the Dali by Lulu safety report

How do I install Dali by Lulu?

It runs remotely at dali.getlulu.dev. Add it to Claude Code, Cursor, VS Code or Claude Desktop with the snippets above, or call it through the mcp.market gateway without installing anything.

Does Dali by Lulu need an API key?

Not as far as the registry entry and our scan can tell: no credentials are declared or required.

Is Dali by Lulu maintained?

The last commit was 125 days ago (2026-07-13). The latest release is v0.6.1.

Is Dali by Lulu up?

0% of our last 28 checks got an answer. We check remote servers about four times a day.

What can I use instead of Dali by Lulu?

Servers from other publishers that do the same job: Decionis MCP server, Agent-Native Slides MCP server and PaperBanana MCP server.

How does Dali by Lulu compare with other AI and agents MCP servers?

safety score 54/100 (higher than 13% of 4,456 AI and agents servers); tools 16 (the typical AI and agents server has 7); tools that change things 0% (typical: 3%. Fewer write tools means less an agent can break). Full comparison.