Freesound MCP Server
Integrates with Freesound.org to enable searching, discovering, and previewing audio content such as sound effects and music loops. It provides detailed metadata and licensing information to support video editing and content creation workflows.
README
Freesound MCP Server
A Model Context Protocol (MCP) server that integrates with Freesound.org, enabling AI agents to search and discover audio content for video editing and content creation workflows.
Features
The Freesound MCP Server enables AI assistants to:
- Search Audio Content: Find sound effects, ambient sounds, and music loops using natural language queries
- Access Metadata: Get detailed information about audio files including duration, tags, licensing, and descriptions
- Preview Content: Access preview URLs for immediate audio playback evaluation
- License Compliance: Retrieve licensing information to ensure proper attribution and usage rights
Installation
Prerequisites
You will need to obtain a Freesound API key:
- Create an account at Freesound.org
- Apply for an API key at https://freesound.org/api/apply/
- Once approved, note your API key for configuration
Docker Installation (Recommended)
The easiest way to run the Freesound MCP Server is using Docker. No local Python installation required.
Setup
- Clone the repository:
git clone https://github.com/johnkimdw/freesound-mcp-server.git
cd freesound-mcp-server
- Build docker image:
docker build -t freesound-mcp .
Claude Desktop
Add the following configuration to your Claude Desktop config file:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"freesound": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"FREESOUND_API_KEY",
"freesound-mcp"
],
"env": {
"FREESOUND_API_KEY": "<YOUR_FREESOUND_API_KEY>"
}
}
}
}
Local Installation
If you prefer not to use Docker, you can install and run the server locally using Python and uv.
Requirements
- Python 3.10+
- uv package manager
Setup
- Clone the repository:
git clone https://github.com/johnkimdw/freesound-mcp-server.git
cd freesound-mcp-server
- Install dependencies:
uv sync
- Set your API key:
export FREESOUND_API_KEY=your_api_key_here
Claude Desktop Configuration
{
"mcpServers": {
"freesound": {
"command": "/path/to/uv",
"args": [
"--directory",
"/path/to/freesound-mcp-server",
"run",
"freesound-mcp"
],
"env": {
"FREESOUND_API_KEY": "<YOUR_FREESOUND_API_KEY>"
}
}
}
}
Usage
Once configured, you can interact with the Freesound MCP Server through your AI assistant. Here are some example queries:
- "Find thunder sound effects for a storm scene"
- "Search for ambient city sounds under 30 seconds"
- "Look for piano music loops with Creative Commons licensing"
- "Find dog barking sound effects"
- "Search for ocean waves background audio"
Available Tools
search_sounds
Search for audio files on Freesound.org using natural language queries.
Parameters:
query(string, required): Search terms for audio contentmax_results(integer, optional): Number of results to return (1-30, default: 10)
Returns:
- Audio file metadata including:
- File name and description
- Duration and file format
- Tags and categories
- License information
- Preview URLs (high and low quality)
- Uploader information
- Direct links to Freesound.org pages
Transport Options
The server supports multiple transport methods for different deployment scenarios:
Stdio Transport (Default)
Used for local integration with Claude Desktop and other MCP clients:
uv run freesound-mcp
# python -m freesound_mcp.server --transport stdio
<!--
HTTP Transport
For web integration or custom deployments:
python -m freesound_mcp.server --transport http --port 8000
Streamable HTTP Transport
For advanced streaming scenarios:
python -m freesound_mcp.server --transport streamable-http --port 8000
``` -->
## Development
### Building from Source
```bash
# Clone the repository
git clone https://github.com/yourname/freesound-mcp-server.git
cd freesound-mcp-server
# Install dependencies
uv sync
# Run tests
uv run pytest
# Build Docker image
docker build -t freesound-mcp .
Testing
Use the MCP Inspector for detailed debugging:
npx @modelcontextprotocol/inspector uv run freesound-mcp
Licensing and Attribution
This MCP server respects Freesound.org's terms of service and API usage guidelines. All audio content retrieved through this server:
- Originates from Freesound.org and is subject to their licensing terms
- Requires proper attribution as specified by individual file licenses
- Should be used in compliance with Creative Commons and other applicable licenses
Important: Always review the licensing information provided with each audio file to ensure compliance with attribution requirements and usage restrictions.
Error Handling
The server includes comprehensive error handling for common scenarios:
- Invalid API Key: Clear error messages when authentication fails
- Rate Limiting: Automatic handling of API rate limits with appropriate error responses
- Network Issues: Timeout handling and connection error management
- Invalid Queries: Input validation and sanitization
Configuration
Environment Variables
FREESOUND_API_KEY(required): Your Freesound.org API key
Advanced Configuration
For advanced users, additional configuration options are available through command-line arguments:
python -m freesound_mcp.server --help
License
This project is licensed under the MIT License - see the LICENSE file for details.
The audio content accessed through this server is provided by Freesound.org and is subject to individual Creative Commons and other open licenses as specified by content creators.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.