Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"clarifyprompt": {
"env": {
"LLM_MODEL": "qwen2.5:7b",
"LLM_API_URL": "http://localhost:11434/v1"
},
"args": [
"-y",
"clarifyprompt-mcp"
],
"command": "npx"
}
}
}Are you the author?
Add this badge to your README to show your security score and help users find safe servers.
A context-aware MCP prompt compiler that transforms vague prompts into platform-optimized prompts for 58+ AI platforms across 7 categories — grounded in your workspace signals (CLAUDE.md, AGENTS.md, .cursorrules, package.json), resolved intent, and the capabilities of the target model.
Run this in your terminal to verify the server starts. Then let us know if it worked — your result helps other developers.
npx -y 'clarifyprompt-mcp' 2>&1 | head -1 && echo "✓ Server started successfully"
After testing, let us know if it worked:
Five weighted categories — click any category to see the underlying evidence.
No known CVEs.
Checked clarifyprompt-mcp against OSV.dev.
Be the first to review
Have you used this server?
Share your experience — it helps other developers decide.
Sign in to write a review.
Others in ai-ml / writing
Persistent memory using a knowledge graph
Dynamic problem-solving through sequential thought chains
Workspace template + MCP server for Claude Code, Codex CLI, Cursor & Windsurf. Multi-agent knowledge engine (ag-refresh / ag-ask) that turns any codebase into a queryable AI assistant.
Privacy-first. MCP is the protocol for tool access. We're the virtualization layer for context.
MCP Security Weekly
Get CVE alerts and security updates for Clarifyprompt MCP Server and similar servers.
Start a conversation
Ask a question, share a tip, or report an issue.
Sign in to join the discussion.
A context-aware MCP prompt compiler that transforms vague prompts into platform-optimized prompts for 60+ AI platforms across 7 categories — grounded in your workspace signals (CLAUDE.md, AGENTS.md, .cursorrules, package.json), resolved intent, and the capabilities of the target model.
Send a raw prompt. ClarifyPrompt gathers the right context, resolves what you're actually trying to do, and returns a version specifically optimized for Midjourney, DALL-E, Sora, Runway, Higgsfield, ElevenLabs, Claude, ChatGPT, Cursor, or any of the 60+ supported platforms — with the right syntax, parameters, structure, and grounding.
New in 1.6.4: Documentation and process cleanup — the separate
clarifyprompt-packsregistry was archived and its content consolidated back into this repo underpacks/, now the single source of truth for both knowledge packs and platform packs. New top-level Knowledge packs section in the README explains the loading + authoring model. No engine code, MCP tool, or platform changes. See CHANGELOG.md.
You write: "a dragon flying over a castle at sunset"
ClarifyPrompt returns (for Midjourney):
"a majestic dragon flying over a medieval castle at sunset
--ar 16:9 --v 6.1 --style raw --q 2 --chaos 30 --s 700"
ClarifyPrompt returns (for DALL-E):
"A majestic dragon flying over a castle at sunset. Size: 1024x1024"
Same prompt, different platform, completely different output. ClarifyPrompt knows what each platform expects — and in 1.2.0, it also knows what you're working on.
Docs + process patch. No engine, MCP tool, or platform changes — but a meaningful cleanup of the pack-distribution model.
LumabyteCo/clarifyprompt-packs (the separate community-pack registry created in 1.3 with the right principle but at the wrong scale) has been archived. Its three starter packs already lived in this repo's packs/ folder; the registry was meant to be the canonical home but in practice everything always shipped from here via the npm tarball. The drift caught up: higgsfield-creative-handbook shipped in 1.6.2 and never made it to the registry, even though the registry's own README told users to fetch packs from there.
Net result of 1.6.4:
packs/*.md knowledge packs + packs/platforms/*.yaml platform configs all live in clarifyprompt-mcp and ship in the npm tarball.load_knowledge_pack({source: "<url-or-path>", scope: ...})), the three starter packs + Higgsfield, the scope semantics, and how to contribute.packs/README.md — pack authoring guide (frontmatter schema, chunk boundaries, quality bar). Lifted from the archived registry so the content isn't lost.clarifyprompt-packs lands on a banner pointing here.When there's a forcing function: a community PR queue on packs alone, pack count >20, or divergent licensing/governance. Until then the maintenance cost of keep