Promptibus MCP
Promptibus MCP is a model intelligence server that provides structured knowledge about generative AI models, helping AI agents understand how to use, format, and select the right models for their tasks.
Recommend a model: Find the best AI model for a given task, with optional domain filtering (IMAGE, VIDEO, TEXT, CODE, AUDIO) and constraints like budget or speed — returns top 3 options with reasoning and parameters.
Format/optimize a prompt: Take a raw prompt and optimize it for a specific model by applying model-specific syntax, parameters, and best practices.
Validate a prompt: Check a prompt against a model's rules to catch errors like deprecated flags, invalid parameters, or length violations.
Compare models: Get a side-by-side comparison of 2–5 models on dimensions like provider, domain, cost, and capabilities, with optional focus criteria (e.g., photorealism, speed).
Get model parameters: Retrieve recommended parameters for a model, including defaults, ranges, and community-tested configurations, optionally filtered by task type.
Get a full model profile: Access a complete profile including capabilities, syntax guide, parameters, community tips, and related prompts — also available as Markdown via
promptibus://models/{slug}.Access system prompts: List or retrieve curated system prompts by slug.
Provides structured knowledge about ElevenLabs audio generation models, including prompt formatting, parameter recommendations, and model-specific capabilities for AI agents.
Provides structured knowledge about Suno audio generation models (v4, v3.5), including prompt formatting, parameter recommendations, and model-specific capabilities for AI agents.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Promptibus MCPrecommend a model for creating a photorealistic portrait"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
@promptibus/mcp — model intelligence for AI agents
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
See it in action
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-2The 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.
Why use this
Stops hallucination. Your agent answers from a curated DB of 67+ models, not from training data that's 6 months stale.
Real money, real choices.
get_pricing({ model: "dall-e-3", volume: 100 })returns actual USD cost plus cheaper alternatives — agents can finally optimize for budget, not just "vibes."Right model for the job.
recommend_modelranks across all five domains (image / video / audio / text / code) with reasoning, not guessing.Lint before you generate.
lint_promptcatches deprecated flags, invalid parameters, and length violations before you burn credits.Zero friction. Works anonymously without an account.
npx -y @promptibus/mcp— that's the install.
Install in 30 seconds
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.
Tools
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 |
| Top 3 models for a task, with reasoning + cost. |
|
| Reformats a prompt for a specific model — applies model-specific syntax + community-tested wording. |
|
| Finds deprecated flags, invalid parameters, length violations. Suggests fixes. |
|
| Side-by-side: provider, domain, cost, capabilities. 2–5 models. |
|
| Recommended parameters: defaults, ranges, community configs. |
|
| Full profile: capabilities, syntax guide, parameters, community tips, related prompts. |
|
| Real USD pricing for a model / domain / planned volume. Includes cheaper alternatives. |
|
Use cases
"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.
Resources
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.
Prompts
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 textPlans & rate limits
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.
Authentication
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 |
| No | Higher rate limits, full model coverage. Get one at promptibus.com/settings/api-keys. |
| No | Override the API base (default |
FAQ
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.
Caching
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).
Privacy
HTTPS to
promptibus.com; no third-party trackers in the request pathAPI keys hashed server-side (SHA-256)
Anonymous usage rate-limited by IP
No client-side database, no local state beyond a single HTTP client
Client configs
The 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/mcpSupported models
67+ models across 5 domains. Highlights:
IMAGE — Midjourney v7 / v6.1 · FLUX 2 Pro / 1.1 Pro · Stable Diffusion 3.5 · DALL-E 3 · GPT Image 1 · Ideogram 3 · Recraft V4 Pro · Imagen 4 Ultra · Leonardo Phoenix
VIDEO — Sora · Runway Gen-3 / Gen-4 · Kling 2.5 · Pika 3 · Luma Dream Machine · Hailuo · Seedance 2 · Veo 2 · LTX 2.3 · Helios
AUDIO — Suno v4 / v5 · Udio 2 · ElevenLabs · Hume AI · Stable Audio 2 · MusicGen · ACE-Step
TEXT — GPT-5 / 5.4 · Claude 4 Opus / Sonnet · Claude Sonnet 4.6 · Gemini 3.1 Pro / 2.5 Pro · DeepSeek R2 · Llama 4 Maverick · Grok 3
CODE — Claude Code · Cursor · Windsurf · Codex CLI · Devin · Augment Code · Aider · Copilot · DeepSeek V3 · Nemotron 3 Super
Full catalogue: promptibus.com/models.
⭐ Help others find this
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.
Links
Website: promptibus.com
All models: promptibus.com/models
API keys: promptibus.com/settings/api-keys
Pricing: promptibus.com/pricing
Issues: github.com/promptibus/mcp/issues
Main app source: github.com/promptibus/promptibus
MCP spec: modelcontextprotocol.io
License
MIT — © Promptibus
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