Dali by Lulu
REMOTE · DALI.GETLULU.DEV · 2 COMPONENTS · SCANNED AUG 3
The prediction MCP — score your prompt before you generate, so you never waste a credit.
Available components
How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. How we score →
Endpoint Security57
- The endpoint's TLS certificate is valid, in date, and uses a strong key. View diagnostics → Pass
- Authorisation not fully verified: no authorisation is required to call this server, and 16 tool(s) never declared a destructiveHint. The MCP spec treats an absent hint as destructive by default, so we cannot call this surface safe. See how to fix → View diagnostics → Unverified
- HTTPS is enforced; there's no plaintext access path. View diagnostics → Pass
- HSTS check failed: the Strict-Transport-Security header is absent. See how to fix → View diagnostics → Fail
- DNSSEC check failed: this domain isn't protected by DNSSEC. See how to fix → View diagnostics → Fail
Transport & Reachability100
- Verified streamable-http transport via a live MCP handshake. View diagnostics → Pass
Schema Quality & AI Usability24
- 0% of prompts and resources have a non-trivial description (not blank, and not just the item's name).Fail
- AI-judged instruction clarity (fair).Partial
- Context-footprint check failed: tool/resource definitions use about 3108 tokens (~172/item across 18 items; 16 tools + 2 resources), over budget; trim descriptions and params. See how to fix → Fail
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management27
- Stability observed for 8 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage77
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 21% of tool parameters carry a description.Partial
- Structured output schemas are declared (94% of tools); any adoption earns full credit.Pass
Capabilities100
- Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
- Supports UI / widget rendering.Pass
Add this component to your MCP client. Where a client-specific snippet is available, pick your client below and copy it straight into your config; otherwise use the connection detail shown.
remote · dali.getlulu.dev
claude mcp add --transport http lulu-the-narwhal-dali https://dali.getlulu.dev/mcp
[mcp_servers.lulu-the-narwhal-dali] url = "https://dali.getlulu.dev/mcp"
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"lulu-the-narwhal-dali": {
"type": "remote",
"url": "https://dali.getlulu.dev/mcp",
"enabled": true
}
}
} openclaw mcp add lulu-the-narwhal-dali --url https://dali.getlulu.dev/mcp --transport streamable-http
mcp_servers:
lulu-the-narwhal-dali:
url: "https://dali.getlulu.dev/mcp" {
"mcpServers": {
"lulu-the-narwhal-dali": {
"type": "http",
"url": "https://dali.getlulu.dev/mcp"
}
}
} The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.
Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 2 Aug 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 20 to 23. That category is still filling its 30-day observation window: 6 days of observed history at the previous scan, 7 at this one. The score rises as the window fills, whether or not the server changes.
- 31 Jul 26 +4
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
- 29 Jul 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 7 to 10. That category is still filling its 30-day observation window: 2 days of observed history at the previous scan, 3 at this one. The score rises as the window fills, whether or not the server changes.
- 28 Jul 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 3 to 7. That category is still filling its 30-day observation window: 1 days of observed history at the previous scan, 2 at this one. The score rises as the window fills, whether or not the server changes.
- 27 Jul 26 0
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
- 26 Jul 26 47
First indexed and scored.
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 3 Aug 2026 · Probed https://dali.getlulu.dev/mcp
TLS valid
Negotiated TLS 1.3 with TLS_AES_128_GCM_SHA256 .
| Subject | Issuer | Valid from | Valid until | Key | Signature | Serial |
|---|---|---|---|---|---|---|
| CN=dali.getlulu.dev | CN=WR3,O=Google Trust Services,C=US | 7 Jul 2026 | 5 Oct 2026 | RSA 2048 | SHA256-RSA | 8ad6d29b71caa7320a074a81229138e1 |
| SANs: dali.getlulu.dev | ||||||
| CN=WR3,O=Google Trust Services,C=US (CA) | CN=GTS Root R1,O=Google Trust Services LLC,C=US | 13 Dec 2023 | 20 Feb 2029 | RSA 2048 | SHA256-RSA | 7ff005a91568d63abc22861684aa4b5a |
| CN=GTS Root R1,O=Google Trust Services LLC,C=US (CA) | CN=GlobalSign Root CA,OU=Root CA,O=GlobalSign nv-sa,C=BE | 19 Jun 2020 | 28 Jan 2028 | RSA 4096 | SHA256-RSA | 77bd0d6cdb36f91aea210fc4f058d30d |
DNSSEC insecure
Validation of dali.getlulu.dev. — Not signed
| Zone | DS | Keys | Algorithms | Outcome |
|---|---|---|---|---|
| . | trust_anchor | 20326, 38696 | 8, 8 | Verified |
| dev. | present | 60074 | 8 | Verified |
| getlulu.dev. | absent | Unsigned (proven) parent-signed NSEC/NSEC3 proves an unsigned delegation |
Authentication No authorisation required
The endpoint answered without asking for a token. Anyone who knows the URL can reach it.
| Result | No authorisation required |
|---|---|
| HTTP status | 200 |
Transports 2 probes
| Transport | URL | Outcome | Status | Location |
|---|---|---|---|---|
| streamable-http | https://dali.getlulu.dev/mcp | Verified | 200 | |
| http (plaintext) | http://dali.getlulu.dev/mcp | HTTPS enforced | 301 | https://dali.getlulu.dev:443/mcp |
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability.
analyze_intent ~32
Parse a creative prompt into structured intent dimensions.
| Name | Type | Req | Description |
|---|---|---|---|
| medium | string | — | — |
| prompt | string | yes | — |
Structured output declared, but exposes no named fields.
No examples provided.
analyze_winning_formula ~235
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)
| Name | Type | Req | Description |
|---|---|---|---|
| category | string | — | — |
| csv | string | yes | — |
| string | — | — |
Structured output declared, but exposes no named fields.
No examples provided.
community_benchmark ~52
Compare your prompt against community top scorers for this generator. Returns your score, missing A-grade patterns, and highest-ROI patterns to add.
| Name | Type | Req | Description |
|---|---|---|---|
| generator | string | yes | — |
| prompt | string | yes | — |
Structured output declared, but exposes no named fields.
No examples provided.
creative_patterns ~70
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.
| Name | Type | Req | Description |
|---|---|---|---|
| generator | string | yes | — |
| grade | string | — | — |
Structured output declared, but exposes no named fields.
No examples provided.
dali_version ~42
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.
Input schema present but exposes no named parameters.
Structured output declared, but exposes no named fields.
No examples provided.
enhance_prompt ~169
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.
| Name | Type | Req | Description |
|---|---|---|---|
| category | string | — | — |
| generator | string | yes | — |
| prompt | string | yes | — |
Structured output declared, but exposes no named fields.
No examples provided.
enhancement_path ~160
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
| Name | Type | Req | Description |
|---|---|---|---|
| generator | string | yes | The generation model (veo3, seedance, kling, etc.) |
| starting_grade | string | — | The grade you're starting from — 'F', 'D', or 'C' (default 'F') |
Structured output declared, but exposes no named fields.
No examples provided.
list_generators ~25
List all supported generation targets (providers + models) with medium and core strength.
Input schema present but exposes no named parameters.
Structured output declared, but exposes no named fields.
No examples provided.
my_story ~27
Your Dali creative report — scoring history, generator stats, recent scorers, creative DNA.
Input schema present but exposes no named parameters.
Structured output declared, but exposes no named fields.
No examples provided.
prompt_neighbors ~142
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
| Name | Type | Req | Description |
|---|---|---|---|
| generator | string | yes | The generation model (veo3, midjourney, flux, etc.) |
| prompt | string | yes | The prompt to find neighbors for. |
Structured output declared, but exposes no named fields.
No examples provided.
score_creative ~351
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.
| Name | Type | Req | Description |
|---|---|---|---|
| category | string | — | — |
| image_url | string | yes | — |
Structured output declared, but exposes no named fields.
No examples provided.
score_creative_from_view ~449
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.
| Name | Type | Req | Description |
|---|---|---|---|
| category | string | yes | — |
| defects | — | — | — |
| dominant_emotion | string | — | — |
| eye_contact | boolean | — | — |
| format | string | — | — |
| lighting | string | — | — |
| offer_visible | boolean | — | — |
| subject | string | — | — |
| subject_age | string | — | — |
| text_density | string | — | — |
Structured output declared, but exposes no named fields.
No examples provided.
score_prompt ~247
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…
| Name | Type | Req | Description |
|---|---|---|---|
| category | string | — | — |
| generator | string | yes | — |
| prompt | string | yes | — |
No output schema declared.
No examples provided.
score_variations ~105
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.
| Name | Type | Req | Description |
|---|---|---|---|
| generator | string | yes | Target generator for all variants |
| prompts | array | yes | List of 2–8 prompt variants (same creative intent, different wording) |
Structured output declared, but exposes no named fields.
No examples provided.
suggest_generator ~110
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.
| Name | Type | Req | Description |
|---|---|---|---|
| budget_usd_max | number | — | Max USD per generation attempt (default $1.00) |
| concept | string | yes | What you want to make — subject, style, mood, format, use case |
Structured output declared, but exposes no named fields.
No examples provided.
track_enhancement ~103
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.
| Name | Type | Req | Description |
|---|---|---|---|
| enhanced_prompt | string | yes | — |
| generator | string | yes | — |
| original_prompt | string | yes | — |
Structured output declared, but exposes no named fields.
No examples provided.