What can elevenlabs-mcp do?

text-to-speech synthesis via mcp protocol, voice selection and management via mcp, mcp protocol server implementation for elevenlabs, audio generation with configurable synthesis parameters, error handling and api response translation, authentication and credential management

elevenlabs-mcp

MCP ServerFree

MCP server: elevenlabs-mcp

Open Source

/ 100

6 capabilities

Capabilities6 decomposed

text-to-speech synthesis via mcp protocol

Medium confidence

Exposes ElevenLabs text-to-speech API as an MCP tool, allowing Claude and other MCP clients to invoke voice synthesis without direct API integration. The server translates MCP tool calls into ElevenLabs HTTP requests, handles authentication via API key, and streams or returns audio file references. Implements the Model Context Protocol's tool-calling interface to bridge LLM agents with ElevenLabs' neural TTS engine.

Solves for

I want my Claude agent to generate spoken audio from text without writing custom API codeI need to add voice synthesis capabilities to an MCP-compatible applicationI want to chain text generation (from Claude) directly into audio generation in a single workflow

Best for

AI agents and assistants built on Claude or other MCP-compatible LLMs

Teams building multi-modal applications that combine text and speech

Developers integrating ElevenLabs into existing MCP server ecosystems

Requires

ElevenLabs API key (free or paid account)

MCP-compatible client (Claude Desktop, or custom MCP client implementation)

Network connectivity to ElevenLabs API endpoints

Limitations

Requires valid ElevenLabs API key with sufficient quota — no fallback to free tier or alternative providers

Audio output format and quality depend entirely on ElevenLabs' current API capabilities — no local synthesis option

MCP protocol overhead adds latency compared to direct API calls — not suitable for real-time streaming use cases

What makes it unique

Implements ElevenLabs TTS as a native MCP tool, enabling seamless integration into Claude and other MCP clients without custom API wrappers — uses MCP's standardized tool schema to expose voice synthesis as a first-class capability within the protocol

vs alternatives

Simpler than building custom API clients for each LLM platform; more flexible than ElevenLabs' native integrations because it works with any MCP-compatible client, not just specific platforms

voice selection and management via mcp

Medium confidence

Provides MCP tools to list available ElevenLabs voices, retrieve voice metadata (name, language, accent, preview audio), and select voices for synthesis. The server queries ElevenLabs' voice API endpoint and exposes voice information as structured data, allowing agents to programmatically choose voices based on language, gender, or other attributes without hardcoding voice IDs.

Solves for

I want my agent to dynamically select a voice based on the target language or speaker characteristicsI need to list all available voices and their properties so users can choose oneI want to validate that a voice ID exists before attempting synthesis

Best for

Multi-language applications requiring voice selection logic

Interactive applications where users browse and select voices

Agents that need to adapt voice selection based on content or context

Requires

ElevenLabs API key with voice listing permissions

MCP client capable of calling tools and processing structured responses

Limitations

Voice list is cached at server startup — new voices added to ElevenLabs won't appear until server restart

No filtering or search functionality built into the MCP tool — clients must implement their own voice selection logic

Voice metadata (accent, language) is only as accurate as ElevenLabs' API response — no validation or enrichment

What makes it unique

Exposes ElevenLabs voice catalog as queryable MCP tools, enabling agents to discover and reason about available voices programmatically rather than relying on hardcoded voice IDs or external documentation

vs alternatives

More discoverable than static voice ID lists; integrates voice selection directly into agent workflows without requiring separate API calls or manual configuration

mcp protocol server implementation for elevenlabs

Medium confidence

Implements the Model Context Protocol (MCP) server specification, exposing ElevenLabs capabilities as standardized MCP tools and resources. The server handles MCP initialization, tool registration, request routing, and error handling according to the MCP specification. It acts as a bridge between MCP clients (like Claude) and the ElevenLabs API, translating MCP calls into ElevenLabs HTTP requests and returning results in MCP-compliant format.

Solves for

I want to add ElevenLabs to my MCP server ecosystem without writing protocol boilerplateI need a standards-compliant MCP server that works with Claude and other MCP clientsI want to extend this server with additional ElevenLabs capabilities or other integrations

Best for

Developers building MCP server ecosystems

Teams standardizing on MCP for LLM integrations

Organizations using Claude with MCP as their primary integration pattern

Requires

Node.js or Python runtime (depending on implementation language)

MCP SDK or library for the chosen language

ElevenLabs API key

Limitations

MCP protocol version compatibility depends on server implementation — may not support all MCP features (e.g., resources, sampling)

No built-in rate limiting or quota management — relies on ElevenLabs API rate limits

Error handling and retry logic may be minimal — transient failures could cause agent failures without graceful degradation

What makes it unique

Provides a complete MCP server implementation for ElevenLabs, handling all protocol-level concerns (initialization, tool registration, request routing) so developers don't need to implement MCP boilerplate themselves

vs alternatives

More maintainable than custom API wrappers because it adheres to a standard protocol; more flexible than ElevenLabs' native integrations because it works with any MCP client

audio generation with configurable synthesis parameters

Medium confidence

Exposes ElevenLabs TTS synthesis parameters (stability, similarity_boost, style, use_speaker_boost) as configurable MCP tool inputs, allowing agents to fine-tune voice characteristics and synthesis behavior. The server passes these parameters directly to the ElevenLabs API, enabling control over voice consistency, emotional tone, and speaker emphasis without requiring multiple API calls or voice cloning.

Solves for

I want to adjust voice stability and similarity for different use cases (e.g., consistent vs. expressive)I need to control emotional tone or style in synthesized speechI want to enable speaker boost for more natural-sounding output

Best for

Applications requiring fine-grained control over voice characteristics

Agents that adapt synthesis parameters based on content type or context

Teams experimenting with different voice settings for quality optimization

Requires

ElevenLabs API key with access to advanced synthesis parameters

MCP client capable of passing structured parameters to tools

Limitations

Parameter support depends on ElevenLabs API version — older API versions may not support all parameters

No validation or guidance on optimal parameter ranges — agents must know valid values or experiment

Parameter effects are not deterministic across different voices — tuning for one voice may not transfer to another

What makes it unique

Exposes ElevenLabs' full parameter set as MCP tool inputs, enabling agents to programmatically control voice characteristics without requiring separate API calls or configuration files

vs alternatives

More flexible than fixed voice presets; allows agents to adapt synthesis behavior dynamically based on content or user preferences

error handling and api response translation

Medium confidence

Translates ElevenLabs API errors and responses into MCP-compliant error messages and structured results. The server catches HTTP errors from ElevenLabs (authentication failures, rate limits, invalid parameters), maps them to appropriate MCP error codes, and returns human-readable error messages to the client. This abstraction shields MCP clients from ElevenLabs API details and enables consistent error handling across the MCP ecosystem.

Solves for

I want clear error messages when ElevenLabs API calls failI need my agent to handle API errors gracefully without crashingI want to distinguish between authentication errors, rate limits, and invalid parameters

Best for

Production applications requiring robust error handling

Agents that need to retry or fall back on API failures

Teams debugging integration issues between MCP and ElevenLabs

Requires

MCP client capable of handling error responses

Understanding of ElevenLabs API error codes and messages

Limitations

Error translation is only as good as the MCP server's implementation — some ElevenLabs errors may not map cleanly to MCP error codes

No built-in retry logic — clients must implement their own retry strategies

Error messages are only as detailed as ElevenLabs' API responses — some errors may lack actionable information

What makes it unique

Provides a translation layer between ElevenLabs API errors and MCP protocol errors, ensuring consistent error handling and enabling agents to reason about failure modes without deep knowledge of ElevenLabs internals

vs alternatives

More robust than direct API error propagation; enables better error recovery and debugging compared to opaque API failures

authentication and credential management

Medium confidence

Manages ElevenLabs API authentication by reading API keys from environment variables, configuration files, or secure credential stores. Implements secure credential handling (no logging of secrets, proper scoping) and validates API key validity before making requests. Provides clear error messages when credentials are missing or invalid, guiding users to set up authentication correctly.

Solves for

I want to securely provide my ElevenLabs API key to the MCP server without hardcoding itI need to validate that my API key is correct before attempting synthesisI want to rotate or update my API key without restarting the MCP server

Best for

Production deployments requiring secure credential management

Teams with multiple environments (dev, staging, prod) needing per-environment keys

Users concerned about API key security and audit trails

Requires

ElevenLabs API key (from https://elevenlabs.io/account/api-keys)

Environment variable or config file setup (ELEVENLABS_API_KEY or similar)

Proper file permissions on config files (if used)

Limitations

API key is typically read once at startup; runtime key rotation requires server restart

No built-in key rotation or expiration management

Credential storage security depends on OS-level security (environment variables, file permissions)

What makes it unique

Implements secure API key management for ElevenLabs, reading credentials from environment or config without exposing them in logs or error messages. Validates credentials at startup and provides clear guidance for setup, reducing common configuration errors.

vs alternatives

Centralized credential management in MCP server eliminates need for clients to handle API keys directly; environment-based configuration follows security best practices, whereas hardcoding keys in client code is a security risk.

Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.

Related Artifactssharing capabilities

Artifacts that share capabilities with elevenlabs-mcp, ranked by overlap. Discovered automatically through the match graph.

MCP Server22

ElevenLabs

** - The official ElevenLabs MCP server

text-to-speech synthesis with voice cloningmultilingual content generation with language-aware voice selectionvoice-library management and voice selectionvoice-to-text transcription with speaker identification

4 shared capabilities

MCP Server36

MiniMax-MCP

Official MiniMax Model Context Protocol (MCP) server that enables interaction with powerful Text to Speech, image generation and video generation APIs.

mcp-standardized text-to-speech synthesis with voice selectionvoice cloning from audio samples via mcplocal audio playback via mcp

3 shared capabilities

MCP Server39

MiniMax-MCP

Official MiniMax Model Context Protocol (MCP) server that enables interaction with powerful Text to Speech, image generation and video generation APIs.

mcp-standardized text-to-speech synthesis with voice selectionvoice library enumeration and metadata retrievalvoice cloning from audio samples with multi-file support

3 shared capabilities

MCP Server23

DAISYS

** - Generate high-quality text-to-speech and text-to-voice outputs using the [DAISYS](https://www.daisys.ai/) platform.

mcp-native text-to-speech synthesis with daisys platform integrationmulti-voice speaker selection and voice parameter configuration

2 shared capabilities

MCP Server20

rime-mcp

ModelContextProtocol server for Rime text-to-speech API

text-to-speech synthesis request handling with streamingmcp-compliant text-to-speech api bridging

2 shared capabilities

MCP Server20

Pollinations

** - Multimodal MCP server for generating images, audio, and text with no authentication required

audio-generation-via-mcp-protocol

1 shared capability

Best For

✓AI agents and assistants built on Claude or other MCP-compatible LLMs
✓Teams building multi-modal applications that combine text and speech
✓Developers integrating ElevenLabs into existing MCP server ecosystems
✓Multi-language applications requiring voice selection logic
✓Interactive applications where users browse and select voices
✓Agents that need to adapt voice selection based on content or context
✓Developers building MCP server ecosystems
✓Teams standardizing on MCP for LLM integrations

Known Limitations

⚠Requires valid ElevenLabs API key with sufficient quota — no fallback to free tier or alternative providers
⚠Audio output format and quality depend entirely on ElevenLabs' current API capabilities — no local synthesis option
⚠MCP protocol overhead adds latency compared to direct API calls — not suitable for real-time streaming use cases
⚠No built-in caching of synthesized audio — repeated requests for identical text will incur API costs
⚠Voice list is cached at server startup — new voices added to ElevenLabs won't appear until server restart
⚠No filtering or search functionality built into the MCP tool — clients must implement their own voice selection logic

Requirements

ElevenLabs API key (free or paid account)MCP-compatible client (Claude Desktop, or custom MCP client implementation)Network connectivity to ElevenLabs API endpointsElevenLabs API key with voice listing permissionsMCP client capable of calling tools and processing structured responsesNode.js or Python runtime (depending on implementation language)MCP SDK or library for the chosen languageElevenLabs API key

Input / Output

Accepts: text (plain string or formatted text), voice ID (ElevenLabs voice identifier), optional parameters (stability, similarity_boost, style, use_speaker_boost), optional filters (language, gender, accent — if supported by ElevenLabs API), MCP protocol messages (tool calls, resource requests), stability (float, typically 0.0-1.0), similarity_boost (float, typically 0.0-1.0), style (enum or string, depending on ElevenLabs API), use_speaker_boost (boolean), ElevenLabs API error responses (HTTP status codes, error messages), environment variable (ELEVENLABS_API_KEY), config file path, API key string (for validation)

Produces: audio file (MP3 or other format depending on ElevenLabs API), audio URL or file reference, structured metadata (duration, voice info, synthesis parameters), structured list of voice objects, voice metadata (ID, name, language, gender, accent, preview URL), MCP protocol responses (tool results, resource data, errors), synthesized audio with applied parameters, metadata about synthesis settings used, MCP error objects with error codes and messages, structured error metadata (error type, cause, suggested remediation), authentication status (valid/invalid), error message if credentials are missing or invalid, no output of actual API key (security)

UnfragileRank

Adoption5%(25% weight)

Quality12%(25% weight)

Ecosystem59%(15% weight)

Match Graph25%(30% weight)

Freshness75%(5% weight)

UnfragileRank is computed from adoption signals, documentation quality, ecosystem connectivity, match graph feedback, and freshness. No artifact can pay for a higher rank.

Type: MCP Server

6 capabilities

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MCP server: elevenlabs-mcp

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Capabilities6 decomposed

text-to-speech synthesis via mcp protocol

Medium confidence

Solves for

Best for

AI agents and assistants built on Claude or other MCP-compatible LLMs

Teams building multi-modal applications that combine text and speech

Developers integrating ElevenLabs into existing MCP server ecosystems

Requires

ElevenLabs API key (free or paid account)

MCP-compatible client (Claude Desktop, or custom MCP client implementation)

Network connectivity to ElevenLabs API endpoints

Limitations

Requires valid ElevenLabs API key with sufficient quota — no fallback to free tier or alternative providers

Audio output format and quality depend entirely on ElevenLabs' current API capabilities — no local synthesis option

MCP protocol overhead adds latency compared to direct API calls — not suitable for real-time streaming use cases

What makes it unique

vs alternatives

Simpler than building custom API clients for each LLM platform; more flexible than ElevenLabs' native integrations because it works with any MCP-compatible client, not just specific platforms

voice selection and management via mcp

Medium confidence

Solves for

Best for

Multi-language applications requiring voice selection logic

Interactive applications where users browse and select voices

Agents that need to adapt voice selection based on content or context

Requires

ElevenLabs API key with voice listing permissions

MCP client capable of calling tools and processing structured responses

Limitations

Voice list is cached at server startup — new voices added to ElevenLabs won't appear until server restart

No filtering or search functionality built into the MCP tool — clients must implement their own voice selection logic

Voice metadata (accent, language) is only as accurate as ElevenLabs' API response — no validation or enrichment

What makes it unique

vs alternatives

More discoverable than static voice ID lists; integrates voice selection directly into agent workflows without requiring separate API calls or manual configuration

mcp protocol server implementation for elevenlabs

Medium confidence

Solves for

Best for

Developers building MCP server ecosystems

Teams standardizing on MCP for LLM integrations

Organizations using Claude with MCP as their primary integration pattern

Requires

Node.js or Python runtime (depending on implementation language)

MCP SDK or library for the chosen language

ElevenLabs API key

Limitations

MCP protocol version compatibility depends on server implementation — may not support all MCP features (e.g., resources, sampling)

No built-in rate limiting or quota management — relies on ElevenLabs API rate limits

Error handling and retry logic may be minimal — transient failures could cause agent failures without graceful degradation

What makes it unique

vs alternatives

More maintainable than custom API wrappers because it adheres to a standard protocol; more flexible than ElevenLabs' native integrations because it works with any MCP client

audio generation with configurable synthesis parameters

Medium confidence

Solves for

Best for

Applications requiring fine-grained control over voice characteristics

Agents that adapt synthesis parameters based on content type or context

Teams experimenting with different voice settings for quality optimization

Requires

ElevenLabs API key with access to advanced synthesis parameters

MCP client capable of passing structured parameters to tools

Limitations

Parameter support depends on ElevenLabs API version — older API versions may not support all parameters

No validation or guidance on optimal parameter ranges — agents must know valid values or experiment

Parameter effects are not deterministic across different voices — tuning for one voice may not transfer to another

What makes it unique

Exposes ElevenLabs' full parameter set as MCP tool inputs, enabling agents to programmatically control voice characteristics without requiring separate API calls or configuration files

vs alternatives

More flexible than fixed voice presets; allows agents to adapt synthesis behavior dynamically based on content or user preferences

error handling and api response translation

Medium confidence

Solves for

Best for

Production applications requiring robust error handling

Agents that need to retry or fall back on API failures

Teams debugging integration issues between MCP and ElevenLabs

Requires

MCP client capable of handling error responses

Understanding of ElevenLabs API error codes and messages

Limitations

Error translation is only as good as the MCP server's implementation — some ElevenLabs errors may not map cleanly to MCP error codes

No built-in retry logic — clients must implement their own retry strategies

Error messages are only as detailed as ElevenLabs' API responses — some errors may lack actionable information

What makes it unique

vs alternatives

More robust than direct API error propagation; enables better error recovery and debugging compared to opaque API failures

authentication and credential management

Medium confidence

Solves for

Best for

Production deployments requiring secure credential management

Teams with multiple environments (dev, staging, prod) needing per-environment keys

Users concerned about API key security and audit trails

Requires

ElevenLabs API key (from https://elevenlabs.io/account/api-keys)

Environment variable or config file setup (ELEVENLABS_API_KEY or similar)

Proper file permissions on config files (if used)

Limitations

API key is typically read once at startup; runtime key rotation requires server restart

No built-in key rotation or expiration management

Credential storage security depends on OS-level security (environment variables, file permissions)

What makes it unique

vs alternatives

Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.

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elevenlabs-mcp

Capabilities6 decomposed

text-to-speech synthesis via mcp protocol

voice selection and management via mcp

mcp protocol server implementation for elevenlabs

audio generation with configurable synthesis parameters

error handling and api response translation

authentication and credential management

Related Artifactssharing capabilities

ElevenLabs

MiniMax-MCP

MiniMax-MCP

DAISYS

rime-mcp

Pollinations

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

Repository Details

About

Categories

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elevenlabs-mcp

Capabilities6 decomposed

text-to-speech synthesis via mcp protocol

voice selection and management via mcp

mcp protocol server implementation for elevenlabs

audio generation with configurable synthesis parameters

error handling and api response translation

authentication and credential management

Related Artifactssharing capabilities

ElevenLabs

MiniMax-MCP

MiniMax-MCP

DAISYS

rime-mcp

Pollinations

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

Repository Details

About

Categories

Alternatives to elevenlabs-mcp

Are you the builder of elevenlabs-mcp?

Get the weekly brief

Data Sources