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mcp

Model intelligence MCP server — syntax, parameters, pricing for 67+ generative AI models (Midjourney, Flux, Suno, Runway, DALL-E, Stable Diffusion). 7 tools for any MCP client.

Install / Use

claude mcp add promptibus -- npx -y github:promptibus/mcp

If the server publishes to npm under a different name, use that package instead — check the repo README.

About this skill
🔌

MCP Server

Model Context Protocol server

Quality Score

78/100

Supported Platforms

Claude Code
Claude Desktop
Cursor
Windsurf

Tags

Our assessment of mcp

mcp scores 78/100 on our quality scale, 792nd of 939 AI & Machine Learning skills we index.

Its MCP Server is 13 KB long, well organised into 18 sections with 14 code examples: a thorough specification that gives an agent plenty to work with.

It has 3 GitHub stars, so there is little community track record yet; judge it on its content.

Substance
30/30
Structure
20/20
Description
15/15
Adoption
3/20
Freshness
11/15

Maintenance, license and trust

  • The repository was last updated about 6 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
  • Our last check on 2026-08-12 found the source still online.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 90/100, with 1 caution from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

mcp compared with similar skills

All 4 of these similar skills score higher than mcp; compare them before choosing.

SkillScoreStarsUpdatedFormat
mcp (this skill)by promptibus7836mo agoMCP Server
Agent-Reachby Panniantong100106.6k5d agoCLAUDE.md
claude-memby thedotmack100105.3ktodayCLAUDE.md
Understand-Anythingby Egonex-AI10089.0k4d agoCLAUDE.md
headroomby headroomlabs-ai10078.3ktodayCLAUDE.md

Frequently asked questions

How do I install mcp?
Run claude mcp add promptibus -- npx -y github:promptibus/mcp. The install tabs above show the steps for each supported agent.
Which AI agents does mcp work with?
It is written for Claude Code, Claude Desktop, Cursor and Windsurf, as a MCP Server file. Other agents that read the same format can often use it too.
Is mcp safe to use?
It is MIT-licensed and scores 90/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is mcp still maintained?
The repository was last updated about 6 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.

@promptibus/mcp — model intelligence for AI agents

npm version npm downloads Smithery License: MIT MCP Powered by Promptibus LobeHub MCP Badge

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-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.

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_model ranks across all five domains (image / video / audio / text / code) with reasoning, not guessing.
  • Lint before you generate. lint_prompt catches 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 | |---|---|---| | 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 } |

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 text

Plans & 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_…[redacted]" }
    }
  }
}

| 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. |

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 path
  • API 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.

<details> <summary><strong>Claude Desktop</strong></summary>

~/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"]
    }
  }
}
</details> <details> <summary><strong>Claude Code</strong></summary>
claude mcp add promptibus -- npx -y @promptibus/mcp
</details> <details> <summary><strong>Cursor</strong></summary>

.cursor/mcp.json (project) or ~/.cursor/mcp.json (global):

{
  "mcpServers": {
    "promptibus": {
      "command": "npx",
      "args": ["-y", "@promptibus/mcp"]
    }
  }
}
</details> <details> <summary><strong>Windsurf</strong></summary>

~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "promptibus": {
      "command": "npx",
      "args": ["-y", "@promptibus/mcp"]
    }
  }
}
</details> <details> <summary><strong>Zed</strong></summary>

settings.json:

{
  "context_servers": {
    "promptibus": {
      "command": {
        "path": "npx",
        "args": ["-y", "@promptibus/mcp"]
      }
    }
  }
}
</details> <details> <summary><strong>Continue.dev</strong></summary>

~/.continue/config.json, under experimental.modelContextProtocolServers:

{
  "transport": {
    "type": "stdio",
    "command": "npx",
    "args": ["-y", "@promptibus/mcp"]
  }
}
</details> <details> <summary><strong>n8n</strong></summary>

In the MCP Client node, set transport to stdio:

Command:   npx
Arguments: -y @promptibus/mcp
</details>

Supported 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](ht

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars3
CategoryAI
Updated5mo ago
Forks2

Languages

JavaScript

Trust signals

90/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

1 low1 info
mcp — MCP Server: Install & Safety Check | SkillAgent