Clarifyprompt-MCP (LumabyteCo/clarifyprompt-mcp) is an MCP server listed on the M8ven Trust Index. M8ven has not graded it: we have no way to read this server ourselves. No publisher has claimed this listing.

C
Emerging
74/100
2 months ago

Clarifyprompt-MCP

An MCP server that transforms vague prompts into platform-optimized prompts for 58 AI platforms across 7 categories. Send a raw prompt. Get back a version specifically optimized for Midjourney, DALL-E, Sora, Runway, ElevenLabs, Claude, ChatGPT, or any of the 58 supported platforms — with the right syntax, parameters, and structure each platform expects.

Emerging. No concerning findings. Grades remain capped until the project builds reputation through adoption. Grades reflect the full trust pyramid: code, verification depth, and reputation. New projects cap at C until adoption is earned.

How we verified

Code Verified⚡ Live Monitored: not connected

Verified is a snapshot. Live keeps it current, and builds your track record.

⚡ Connect GitHub → continuous verification on every pushwhy connect →

Who stands behind it

LumabyteCo

Source: Glama

Is this your MCP?

Claim it to get a verified publisher badge, a free copy of our full audit findings, and direct contact for any high-priority issues we find. Or connect your repo for our deepest verification, Live Monitored: read-only, revoke anytime. What we access →

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// key findings
No credential exfiltration, no sensitive file access, no obfuscation
Static analysis found nothing flowing your secrets to unexpected places.
Open source with a license and README
Anyone can audit the code, the license is declared, and the publisher documents what it does.
🔐
You'll be asked for 5 credentials: EMBED_API_KEY, LLM_API_KEY, OLLAMA_API_KEY, SEARCH_API_KEY, TAVILY_API_KEY
These are read from process.env at runtime. Make sure you trust where they’ll be sent.
// environment variables
To run this server yourself, you supply these values. They go in your own MCP client configuration and stay on your machine. The secret label means the value is sensitive, not that the server mishandles it.
configCLARIFYPROMPT_SUPPRESS_LEGACY_WARNNo Set to 1 to silence the one-line deprecation hint when CLARIFYPROMPT_CONFIG_DIR / CLARIFYPROMPT_DATA_DIR are used.
🔐 secretEMBED_API_KEYNo (1.3.0+) Embedding API key. Defaults to LLM_API_KEY when unset; not needed for local Ollama.
configEMBED_API_URLNo (1.3.0+) Embedding endpoint for memory + knowledge-pack retrieval. Any OpenAI-compatible /v1/embeddings endpoint. Defaults to LLM_API_URL when unset — Ollama users just work.
configEMBED_DIMENSIONNo (1.3.0+) Embedding output dimension. Default: 768. Must match your embedding model (1536 for OpenAI text-embedding-3-small, 1024 for Voyage, etc.).
configEMBED_MODELNo (1.3.0+) Default: nomic-embed-text:v1.5 (768-dim, pull with ollama pull nomic-embed-text). Swap to text-embedding-3-small for OpenAI, voyage-3 for Voyage, embed-english-v3.0 for Cohere.
🔐 secretLLM_API_KEYDepends API key (not needed for local Ollama)
configLLM_API_URL"": "http://localhost:11434/v1",
configLLM_MODEL"": "qwen2.5:7b"
configLLM_TIMEOUT_MSenv-var override on the LLM client. Default stays at 30s; users on slow hosted models can bump it. The eval workflow uses 120s for gpt-4o-mini.
🔐 secretOLLAMA_API_KEY
configOLLAMA_API_URL
🔐 secretSEARCH_API_KEYNo API key for the configured SEARCH_PROVIDER. Not needed for self-hosted SearXNG.
configSEARCH_API_URLNo Search endpoint URL. Only needed for self-hosted SearXNG (point at your instance).
configSEARCH_PROVIDERNo Optional web-search enrichment provider when enrich_context: true. One of tavily (default) \ brave \ serper \ serpapi \ exa \ searxng.
🔐 secretTAVILY_API_KEY
configXDG_DATA_HOME
// quality suggestions

Tool annotations

No tools have read-only/destructive annotations

Add readOnlyHint or destructiveHint annotations to every tool so hosts can warn users before invoking.

All four hints declared on every tool

23/23 tools missing one or more hints — optimize_prompt (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); list_categories (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); list_platforms (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint), +20 more. OpenAI's directory rejects tools where any of the four hints are missing or non-boolean.

For every tool, set all four hints (readOnlyHint, destructiveHint, idempotentHint, openWorldHint) to explicit true/false values that match the handler’s actual behaviour.

Tool inputs are validated

20/23 tool handlers declare input schemas (87%)

Declare an inputSchema with zod/joi/yup on every tool definition.

Tool handlers catch errors

Only 4/23 tool handlers wrap calls in try/catch (17%)

Wrap each tool handler body in try/catch and return a structured error response.

Tests exist

No test files found

Add tests that exercise each declared tool.

Shell command execution

3 child_process calls — runs shell commands

Prefer library functions over shell-outs. If you must shell out, ensure all inputs are properly escaped.

Claim the listing to review these findings one by one and send us a correction where you disagree, straight to the team. Claiming also means we tell you when the grade moves, and reach you first if we find anything urgent.

// full audit trail
The findings above are the summary. The full trail, every check we ran, each deduction, the network hosts observed and the dependency advisories, goes to verified publishers, along with an alert whenever a new one lands. Verified publishers can also review each finding and dispute it in one click. Publisher corrections have sharpened several of our checks this month, because the maintainer knows the codebase better than any scanner.
// improvement guidance — verified publishers only
We have 6 concrete improvements we can share with the publisher of this MCP. Each comes with specific guidance to raise the trust score.
// embed badge in your README
[![M8ven Score](https://m8ven.ai/badge/mcp/lumabyteco-clarifyprompt-mcp-1c8jd7)](https://m8ven.ai/mcp/lumabyteco-clarifyprompt-mcp-1c8jd7)
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commit: 87a9ec5e7008ea595762b7aaba4fdeb488154dc9
code hash: 213446ade1b66e4e092f905963a05f251c6f6dbb4b8bec7268afe26710248782
verified: 6/12/2026, 11:32:47 AM
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