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Model intelligence for AI agents — syntax, params, pricing for 67+ generative AI models.
Model intelligence for AI agents — syntax, params, pricing for 67+ generative AI models.
Valid MCP server (2 strong, 3 medium validity signals). 3 known CVEs in dependencies (0 critical, 3 high severity) Package registry verified. Imported from the Official MCP Registry.
4 files analyzed · 4 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
This plugin requests these system permissions. Most are normal for its category.
Set these up before or after installing:
Environment variable: PROMPTIBUS_API_KEY
Environment variable: PROMPTIBUS_API_URL
Add this to your MCP configuration file:
{
"mcpServers": {
"com-promptibus-mcp": {
"env": {
"PROMPTIBUS_API_KEY": "your-promptibus-api-key-here",
"PROMPTIBUS_API_URL": "your-promptibus-api-url-here"
},
"args": [
"-y",
"@promptibus/mcp"
],
"command": "npx"
}
}
}From the project's GitHub README.
Your agent thinks Midjourney still uses
--v 5. It doesn't — that flag was dropped at v7. It assumes DALL-E 3 and FLUX Schnell cost the same. They differ by ~50×. It confidently writes[Verse]tags for Suno. They were removed in v4.This MCP server fixes that. Real syntax, real prices, real recommendations for 67+ generative AI models — over the Model Context Protocol.
Works with: Claude Desktop · Claude Code · Cursor · Windsurf · Zed · Continue.dev · n8n · any stdio MCP client Domains: image · video · audio · text · code Cost to start: $0, no account, no API key
Your agent receives a brief — "30-second cinematic video of a thunderstorm at sea." — and instead of guessing, calls a tool.
recommend_model({ task: "30s cinematic video, thunderstorm at sea", domain: "VIDEO" })
Top 3 models for: "30s cinematic video, thunderstorm at sea"
1. Runway Gen-4 (Runway)
Domain: VIDEO | Cost: 1 credit | Version: latest
Improved temporal consistency, camera control, up to 20-second coherent clips.
Source: https://promptibus.com/models/runway-gen-4
2. Sora (OpenAI)
Domain: VIDEO | Cost: 1 credit | Version: latest
Cinematic-quality clips from text prompts.
Source: https://promptibus.com/models/sora
3. Veo 2 (Google)
Domain: VIDEO | Cost: 1 credit | Version: latest
High-fidelity clips with cinematic camera control.
Source: https://promptibus.com/models/veo-2
The agent picks one, formats the prompt with optimize_prompt, lints the result with lint_prompt, checks get_pricing for the volume budget — all before a single token of generation cost is spent.
get_pricing({ model: "dall-e-3", volume: 100 }) returns actual USD cost plus cheaper alternatives — agents can finally optimize for budget, not just "vibes."recommend_model ranks across all five domains (image / video / audio / text / code) with reasoning, not guessing.lint_prompt catches deprecated flags, invalid parameters, and length violations before you burn credits.npx -y @promptibus/mcp — that's the install.Option A — Smithery (recommended):
Visit smithery.ai/server/@promptibus/mcp, pick your client, click install.
Option B — drop into your client's MCP config:
{
"mcpServers": {
"promptibus": {
"command": "npx",
"args": ["-y", "@promptibus/mcp"]
}
}
}
Option C — hosted HTTP endpoint (no install at all):
For clients that support HTTP transport:
{
"mcpServers": {
"promptibus": {
"url": "https://promptibus.com/api/mcp"
}
}
}
Per-client paths are listed under Client configs below.
Every tool is available on every tier — including anonymous. Tiering applies to daily request limits and which models you can query against (free-tier covers 10 popular models; Pro/Studio unlocks all 67+).
| Tool | What it does | Example |
|---|---|---|
recommend_model | Top 3 models for a task, with reasoning + cost. | { task: "logo with embedded text", domain: "IMAGE" } |
optimize_prompt | Reformats a prompt for a specific model — applies model-specific syntax + community-tested wording. | { text: "a cat in space", model: "midjourney-v7" } |
lint_prompt | Finds deprecated flags, invalid parameters, length violations. Suggests fixes. | { prompt: "a cat --ar 16:9", model: "flux-2-pro" } |
compare_models | Side-by-side: provider, domain, cost, capabilities. 2–5 models. | { models: ["flux-2-pro","midjourney-v7"], criteria: "photorealism" } |
get_parameters | Recommended parameters: defaults, ranges, community configs. | { model: "stable-diffusion-3-5", task_type: "portrait" } |
get_model_profile | Full profile: capabilities, syntax guide, parameters, community tips, related prompts. | { model: "suno-v4" } |
get_pricing | Real USD pricing for a model / domain / planned volume. Includes cheaper alternatives. | { model: "dall-e-3", volume: 100 } |
"Which video model gives me the longest single shot under $10?"
→ get_pricing({ domain: "VIDEO", volume: 60 }) returns a sorted matrix; agent picks the cheapest that meets duration.
"Convert this DALL-E prompt to Midjourney v7 syntax."
→ optimize_prompt({ text: "...", model: "midjourney-v7" }) reformats — proper aspect-ratio flag, no --v, model-specific suffixes applied.
"Will this Suno prompt work with v4?"
→ lint_prompt({ prompt: "[Verse] ...", model: "suno-v4" }) flags [Verse] as deprecated and proposes the v4 structure.
"I need to generate 1000 images at the cheapest viable quality."
→ recommend_model filters by domain + budget; get_pricing validates total cost; agent ships under budget.
Browsable model profiles as MCP resources:
promptibus://models/{slug}
Each resource returns a Markdown profile (provider, domain, version, pricing, full guide). Useful for agents that want to surface model info as a sidebar.
The system-prompt MCP prompt exposes curated system prompts from the Promptibus community.
system-prompt # lists all available
system-prompt { "slug": "midjourney-prompt-architect" } # returns full text
Anonymous users get full tool access — no account needed. Limits + model coverage scale with plan.
| Plan | Daily requests | Model coverage |
|---|---|---|
| Anonymous (no key) | 25 | 10 free-tier models |
| Free (with key) | 100 | 10 free-tier models |
| Pro | 500 | All 67+ models |
| Studio | 2,000 | All 67+ models |
Limits reset daily at midnight UTC. Plans + signup at promptibus.com/pricing.
Set PROMPTIBUS_API_KEY in your client config:
{
"mcpServers": {
"promptibus": {
"command": "npx",
"args": ["-y", "@promptibus/mcp"],
"env": { "PROMPTIBUS_API_KEY": "psy_your_api_key_here" }
}
}
}
| Variable | Required | Purpose |
|---|---|---|
PROMPTIBUS_API_KEY | No | Higher rate limits, full model coverage. Get one at promptibus.com/settings/api-keys. |
PROMPTIBUS_API_URL | No | Override the API base (default https://promptibus.com). For self-hosted Promptibus or staging. |
Does this generate images, video, or audio? No. It tells your agent how to use whatever generation API the agent already has access to. Think of it as a prompt engineering co-pilot, not a router.
Do I need an account to start? No. Anonymous mode works out of the box (25 req/day, free-tier models). API key raises limits and unlocks all 67+ models.
Are my prompts logged?
Tool requests transit promptibus.com over HTTPS. We don't persist prompt bodies. API keys are SHA-256 hashed server-side; the raw key never lands in logs.
How fresh is the model data? Community-curated. New models typically appear within days of release; pricing is reviewed monthly. The data lives in a Postgres-backed catalogue at promptibus.com/models.
Does it work offline? The MCP server runs locally; the catalogue lives at promptibus.com. So: agent ↔ MCP server is local stdio, MCP server ↔ Promptibus is HTTPS. No internet, no answers.
Can I self-host the catalogue?
Yes. The Promptibus app is open-source — clone promptibus/promptibus, point PROMPTIBUS_API_URL at your deployment.
Is there an HTTP transport instead of stdio?
Yes — point your client at https://promptibus.com/api/mcp. Useful for sandboxed environments, browser-based MCP clients, and CI.
The client caches responses for tools whose output rarely changes (get_model_profile, get_parameters, compare_models, get_pricing). TTL: 24 h, in-memory per process. Cache is bypassed for tools whose output is input-dependent (recommend_model, optimize_prompt, lint_prompt).
promptibus.com; no third-party trackers in the request pathThe same npx -y @promptibus/mcp command works for every stdio client. Only the config file location and JSON shape differ.
~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):
{
"mcpServers": {
"promptibus": {
"command": "npx",
"args": ["-y", "@promptibus/mcp"]
}
}
}
claude mcp add promptibus -- npx -y @promptibus/mcp
.cursor/mcp.json (project) or ~/.cursor/mcp.json (global):
{
"mcpServers": {
"promptibus": {
"command": "npx",
"args": ["-y", "@promptibus/mcp"]
}
}
}
~/.codeium/windsurf/mcp_config.json:
{
"mcpServers": {
"promptibus": {
"command": "npx",
"args": ["-y", "@promptibus/mcp"]
}
}
}
settings.json:
{
"context_servers": {
"promptibus": {
"command": {
"path": "npx",
"args": ["-y", "@promptibus/mcp"]
}
}
}
}
~/.continue/config.json, under experimental.modelContextProtocolServers:
{
"transport": {
"type": "stdio",
"command": "npx",
"args": ["-y", "@promptibus/mcp"]
}
}
In the MCP Client node, set transport to stdio:
Command: npx
Arguments: -y @promptibus/mcp
67+ models across 5 domains. Highlights:
Full catalogue: promptibus.com/models.
If @promptibus/mcp saves your agent from a wrong-syntax run or a $50 surprise on DALL-E volume, drop a star on the repo. Stars are how new MCP users discover quality servers in a sea of generic wrappers — it costs you a click and the next person ships faster.
MIT — © Promptibus
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