About Resemble AI
The official Resemble AI MCP server gives coding agents queryable product documentation and API specifications, with topic browsing, full-text search, and endpoint lookup.
Key features
- 01Aggregate docs by topic
- 02Search MDX documentation
- 03Retrieve a specific documentation page
- 04Look up OpenAPI endpoint specifications
- 05Search API endpoints
Use cases
- 01Consult voice-cloning guides while building an app
- 02Find documentation for streaming audio implementation
- 03Retrieve API request and response schemas
MCP support
Over stdio, it provides Resemble AI documentation resources and query tools to MCP clients, letting coding agents look up docs and API specifications during development.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://mcp.resemble.ai/mcpclaude mcp add --transport http resemble-ai-resemble https://mcp.resemble.ai/mcp{"mcpServers":{"resemble-ai-resemble":{"type":"http","url":"https://mcp.resemble.ai/mcp"}}}Open in Cursor{"servers":{"resemble-ai-resemble":{"type":"http","url":"https://mcp.resemble.ai/mcp"}}}Open in VS Code{"mcpServers":{"resemble-ai-resemble":{"type":"http","url":"https://mcp.resemble.ai/mcp"}}}{"mcpServers":{"resemble-ai-resemble":{"serverUrl":"https://mcp.resemble.ai/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
https://mcp.resemble.ai/mcphttps://mcp.resemble.ai/sseTools
18| Parameter | Type | Required | Description |
|---|---|---|---|
| url | string | Yes | |
| visualize | boolean | No | |
| model_type | string | No | |
| max_wait_seconds | integer | No | |
| run_intelligence | boolean | No | |
| use_ood_detector | boolean | No | |
| use_reverse_search | boolean | No | |
| zero_retention_mode | boolean | No | |
| audio_source_tracing | boolean | No |
Details
From the project READMEResemble AI MCP Server
Official MCP server exposing Resemble AI documentation as resources and tools. Connect to Cursor, Claude Code, or any MCP-compatible client to enable your coding assistant to access Resemble AI docs during development.
Overview
This is the official Resemble AI MCP server. It implements the Model Context Protocol (stdio transport) to serve documentation from docs/pages/ as queryable resources. The server aggregates docs by topic and provides full-text search across all MDX files.
What it provides:
- Topic-based documentation aggregation (13 topics: voice-cloning, text-to-speech, agents, etc.)
- Full-text search across all MDX documentation pages
- OpenAPI 3.0 spec with exact request/response schemas for code generation
- Direct page and endpoint access
Once connected, your coding assistant can query Resemble AI documentation programmatically. You can vibe code complete applications—your assistant has instant access to guides, tutorials, and exact API schemas for accurate code generation.
Quick Start
1. Clone & Install
git clone https://github.com/resemble-ai/resemble-mcp.git
cd resemble-mcp
# Create virtual environment
python3 -m venv venv
source venv/bin/activate # Windows: venv\Scripts\activate
# Install dependencies
pip install -r requirements.txt
2. Configure MCP Client
Cursor: Add to ~/.cursor/mcp.json:
{
"mcpServers": {
"resemble-ai-docs": {
"command": "/path/to/resemble-mcp/venv/bin/python",
"args": ["/path/to/resemble-mcp/server.py"]
}
}
}
Claude Code / Claude Desktop: Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or equivalent location for your OS:
{
"mcpServers": {
"resemble-ai-docs": {
"command": "/path/to/resemble-mcp/venv/bin/python",
"args": ["/path/to/resemble-mcp/server.py"]
}
}
}
Note: Use absolute paths. Replace
/path/to/resemble-mcpwith your actual path.
3. Restart Client
Restart your MCP client to load the server. Tools will be available after restart.
Available Tools
resemble_docs_lookup
Returns aggregated documentation for a topic. Accepts topic ID and returns all related pages concatenated.
Parameters:
topic(string, required): One of:voice-cloning,text-to-speech,speech-to-speech,speech-to-text,getting-started,voice-design,streaming,detect,agents,sdks,projects-clips,audio-tools,ssml
Returns: Markdown content with all pages for the topic.
resemble_search
Full-text search across all documentation pages. Returns matching pages with snippets.
Parameters:
query(string, required): Search querylimit(integer, optional): Max results (default: 5)
Returns: List of matching pages with titles, paths, and content snippets.
resemble_get_page
Retrieves a specific documentation page by path.
Parameters:
path(string, required): Page path relative todocs/pages/(e.g.,getting-started/quickstart)
Returns: Full page content in Markdown.
resemble_list_topics
Lists all available topic IDs with descriptions.
Returns: Markdown list of topics.
resemble_api_endpoint
Get detailed OpenAPI specification for a specific API endpoint. Returns exact request/response schemas, parameters, and types.
Parameters:
method(string, required): HTTP method (GET,POST,PUT,PATCH,DELETE)path(string, required): API endpoint path (e.g.,/synthesize,/voices)
Returns: Endpoint specification with schemas, parameters, and response formats.
resemble_api_search
Search the OpenAPI spec for endpoints matching a query.
Parameters:
query(string, required): Search query (e.g.,voice,streaming,agent)
Returns: List of matching endpoints with methods, paths, and summaries.
Usage
Once configured, your coding assistant (Cursor, Claude Code, etc.) can call these tools directly. Example use cases:
Building a voice cloning app:
{
"name": "resemble_docs_lookup",
"arguments": { "topic": "voice-cloning" }
}
Searching for streaming implementation:
{
"name": "resemble_search",
"arguments": { "query": "websocket streaming", "limit": 5 }
}
Getting exact API schema for implementation:
{
"name": "resemble_api_endpoint",
"arguments": { "method": "POST", "path": "/synthesize" }
}
Finding all voice-related API endpoints:
{
"name": "resemble_api_search",
"arguments": { "query": "voice" }
}
Your assistant uses these tools automatically when you ask it to build features. For example, "build me a TTS streaming service" triggers resemble_docs_lookup for the text-to-speech topic, and may use resemble_api_endpoint to get exact request schemas for accurate implementation.
Project Structure
resemble-mcp/
├── server.py # MCP server implementation
├── docs/
│ └── pages/ # MDX documentation files
│ ├── getting-started/ # Auth, quickstart, basics
│ ├── voice-generation/ # TTS, STT, S2S
│ ├── voice-creation/ # Voice cloning, recordings
│ ├── agents/ # AI agents
│ ├── detect/ # Deepfake detection
│ └── guides/ # Step-by-step tutorials
└── openapi/
└── openapi.yml # OpenAPI 3.0 specification
Supported MCP Clients
Works with any client implementing the Model Context Protocol:
- Cursor - AI code editor
- Claude Code - Anthropic's coding agent
- Claude Desktop - Anthropic's desktop app
- Any other MCP-compatible client
Development
The server uses stdio transport (reads from stdin, writes to stdout) as per MCP specification.
# Run server directly (for testing/debugging)
python server.py
Architecture:
- Server implementation:
server.py - Documentation source:
docs/pages/(MDX files) - API specification:
openapi/openapi.yml(OpenAPI 3.0) - Topic definitions: Hardcoded in
TOPICSdict - Search: Full-text search with scoring across docs and OpenAPI endpoints
Troubleshooting
Server not loading:
- Verify absolute paths in MCP config
- Ensure virtual environment is activated
- Check
mcppackage is installed:pip show mcp
Tools not appearing:
- Restart MCP client
- Check client logs for initialization errors
- Verify server starts without errors:
python server.py
Search returns no results:
- Use
resemble_docs_lookupwith topic ID for guaranteed results - Try broader search terms
- Check topic list:
resemble_list_topics
License
MIT License - see LICENSE for details.
Links
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.