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Producer AI MCP Server

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Producer AI MCP Server

Producer AI Music - Free AI Music Generator & Song Maker

MCP Badge License: MIT Read Only Stdio Transport MCP Node

A Model Context Protocol server that exposes the canonical Producer AI knowledge surface — AI music-generation workflows and licensing notes, pricing, docs, FAQ, official links — to MCP-compatible AI clients such as Claude Desktop, Cursor, Windsurf, and Continue. Read-only, no API keys, no quota, ~50 ms cold start.

Official website: https://producerai.online

🎵 About Producer AI

Producer AI is an online AI music generator that accepts a song description or lyric draft and advertises full tracks with vocals, fast generation, and royalty-free output language. The site also publishes its current plans, documentation, and community links.

This MCP exposes the documented music workflow, pricing entry point, and official links as read-only context. It does not generate audio, spend credits, or grant a license; current output rights, quotas, and plan terms must be checked on Producer AI itself.

The generated track, lyric, and commercial-use rules may depend on the live service terms and account plan. Treat the MCP as a guide to the public product surface, not as a legal clearance or a file-delivery API.

Related MCP server: Muse AI Image MCP Server

Tools

get_music_workflow

Return the public music-generation workflow and licensing notes exposed by the site. (Producer AI)

Input: no parameters. Returns: text/markdown.

get_pricing

Return the canonical pricing entry point for Producer AI.

Input: no parameters. Returns: text/markdown.

get_official_links

Return the canonical list of official links for Producer AI (website, support, docs when available).

Input: no parameters. Returns: text/markdown.

Resources

  • site://producerai/music-workflows — Public music-generation workflow, input options, and licensing notes.

  • site://producerai/pricing — Canonical pricing entry point.

  • site://producerai/docs — Canonical documentation entry point.

  • site://producerai/faq — Short FAQ generated from public site metadata.

  • site://producerai/links — Canonical URLs to share with users.

Prompts

tell_me_about_producerai

Summarize what the site is, who it's for, and how it works. — Producer AI

start_music_project_producerai

Plan a music-generation session from a goal or lyric draft. — Producer AI

Installation

Install via Smithery

npx -y @smithery/cli install producerai-mcp --client claude

(Replace claude with cursor, windsurf, or continue for those clients.)

Install from source

git clone https://github.com/rocnubie/producerai-mcp.git
cd producerai-mcp
pnpm install

Then add to your MCP client config (claude_desktop_config.json for Claude Desktop, mcp.json for Cursor / Windsurf / Continue):

{
  "mcpServers": {
    "producerai-mcp": {
      "command": "node",
      "args": [
        "/absolute/path/to/producerai-mcp/src/index.mjs"
      ]
    }
  }
}

Debug with MCP Inspector

npx @modelcontextprotocol/inspector node src/index.mjs

Official Links

Development

pnpm install
pnpm start                 # run the server over stdio

License

MIT

Available Tools

3 tools
get_music_workflowA

Return the public music-generation workflow and licensing notes exposed by the site. (Producer AI)

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Describes the tool as returning public information, implying read-only and no auth required. Adds context beyond annotations (none provided).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence, 14 words, front-loaded with verb and resource. No waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool is simple with zero parameters and no output schema; description provides sufficient context about what is returned.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

No parameters exist, so baseline 4 applies. Description adds no param info, but none needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states it returns the public music-generation workflow and licensing notes. Distinguishes from siblings get_pricing and get_official_links.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit when-to-use or when-not-to-use guidance, but the purpose is straightforward. Sibling tools imply different use cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_pricingA

Return the canonical pricing entry point for Producer AI.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A3.9/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, so the description carries full burden. 'Return' implies read-only, but no details on caching, latency, or side effects are given. For a simple retrieval, this is adequate but minimal.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single, concise sentence with no redundant information. Ideal for a straightforward tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given zero parameters and no output schema, the description is brief. It states what it returns but does not clarify the nature of the 'entry point' (e.g., URL, string, object), leaving some ambiguity for the agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are no parameters, so schema coverage is trivially 100%. The description does not need to add parameter meaning, achieving the baseline score of 4.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it returns the 'canonical pricing entry point for Producer AI', with a specific verb and resource. It naturally distinguishes from sibling tools 'get_music_workflow' and 'get_official_links'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit when-to-use or when-not-to-use guidance is provided. However, the parameterless nature implies it is safe to call when pricing info is needed, and siblings are for different purposes.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 3 tool updatesv0.1.0
    • First observedget_music_workflow
    • First observedget_official_links
    • First observedget_pricing
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TDQS

A3.9/5.0
Disambiguation5/5

Each tool retrieves a distinct type of information: music workflow/licensing, pricing, and official links. There is no ambiguity or overlap.

Naming Consistency5/5

All tool names follow a consistent 'get_' prefix pattern with clear nouns (workflow, pricing, links), making the set predictable.

Tool Count4/5

Three tools is slightly on the low side for a general server, but appropriate for a focused informational service with no interactive features.

Completeness4/5

The tool surface covers the main informational needs (workflow, pricing, links) for Producer AI. Minor gaps could include an FAQ or contact tool, but the set is sufficient for basic reference.

Resources

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