ElevenLabs MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose with no ambiguity. delete_job removes jobs, generate_audio_script creates multi-voice audio from structured input, generate_audio_simple creates basic audio, get_audio_file retrieves audio content, get_voiceover_history accesses job history, and list_voices lists available voices. The two generation tools are clearly differentiated by complexity level.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern throughout: delete_job, generate_audio_script, generate_audio_simple, get_audio_file, get_voiceover_history, list_voices. The naming convention is perfectly uniform with clear action-object relationships and no mixing of styles.
Tool Count5/5
Six tools is an ideal number for this audio generation domain. It provides complete coverage of core workflows (generation, retrieval, management, discovery) without being overwhelming. Each tool earns its place with clear utility in the voiceover job lifecycle.
Completeness5/5
The toolset provides complete CRUD/lifecycle coverage for ElevenLabs voiceover operations: create (two generation tools), read (get_audio_file, get_voiceover_history, list_voices), delete (delete_job). There are no obvious gaps - agents can create audio, retrieve results, manage jobs, and discover available voices.
Average 3.1/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed in the last 6 months
- 0 commits in the last 12 weeks
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- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'generate[s] audio' but lacks details on permissions, rate limits, output format, or side effects. While it implies a creation operation, it doesn't clarify if this is a one-time generation or if audio is saved/stored, leaving significant gaps.
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?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. Every part of the sentence contributes to understanding the tool's function, making it appropriately sized and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of an audio generation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the output is (e.g., file format, URL, or data), error conditions, or behavioral traits like latency or resource usage, leaving the agent with insufficient context for reliable use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters ('text' and 'voice_id') adequately. The description adds minimal value by implying 'plain text' for the 'text' parameter and 'default voice settings' for 'voice_id', but doesn't provide additional syntax or format details beyond what the schema offers.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'generate' and resource 'audio from plain text', specifying the action and input type. It distinguishes from siblings like 'generate_audio_script' by emphasizing 'simple' and 'default voice settings', though it doesn't explicitly contrast with all siblings like 'get_audio_file' or 'list_voices'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It mentions 'default voice settings' but doesn't specify when to choose this over 'generate_audio_script' or other siblings, nor does it indicate prerequisites or exclusions for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action but doesn't describe what 'Get' entails—whether it returns raw audio data, a file URL, or a stream; any authentication or permission requirements; rate limits; or error conditions (e.g., if the job doesn't exist or isn't ready). This leaves significant gaps for a tool that likely involves data retrieval.
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?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse. Every part of the sentence contributes to understanding the tool's function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of retrieving audio content (likely involving binary data or file handling), no annotations, and no output schema, the description is insufficient. It doesn't explain the return type (e.g., audio format, size limits), error handling, or behavioral details like whether it's idempotent or has side effects. This leaves the agent with incomplete information for proper invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the single parameter 'job_id' fully documented in the schema. The description adds no additional meaning beyond implying the job must exist and have an associated audio file, but it doesn't specify format, constraints, or examples. This meets the baseline of 3 since the schema handles the parameter documentation adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and resource ('audio file content') with a specific target ('for a specific job'). It distinguishes from siblings like 'list_voices' or 'get_voiceover_history' by focusing on retrieving actual audio content rather than metadata or lists. However, it doesn't explicitly differentiate from potential similar tools like 'generate_audio_simple' beyond the 'get' vs 'generate' distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a completed job), exclusions (e.g., not for in-progress jobs), or comparisons to siblings like 'get_voiceover_history' (which might retrieve metadata vs content). Usage is implied by the purpose but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It explains the input format but doesn't describe what happens after submission: whether this is an async operation, how to retrieve results, expected output format, error conditions, rate limits, or authentication requirements. For a tool that likely creates audio files, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded with the core purpose. The format explanation is necessary but could be slightly more streamlined. Every sentence serves a purpose, though the JSON example takes significant space that might be better in schema examples.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a generation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (audio file URL? job ID? error messages?), how to handle the output, or any post-generation steps. For a tool that presumably creates audio content, this leaves the agent without crucial information about result handling.
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?
Schema description coverage is 100%, so the schema already documents the single parameter. The description adds valuable context by explaining the two acceptable formats (plain text vs. JSON) and providing a concrete JSON structure example. This goes beyond what the schema provides, though it could elaborate more on when to use each format.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate audio from a structured script with multiple voices and actors.' This specifies the verb ('generate audio'), resource ('structured script'), and key capabilities ('multiple voices and actors'). However, it doesn't explicitly differentiate from sibling tools like 'generate_audio_simple', which likely has a simpler interface.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'generate_audio_simple' or explain scenarios where this more complex script format is preferred over simpler options. There's no context about prerequisites, limitations, or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool deletes a job and associated files, which implies a destructive, irreversible operation. However, it lacks details about permissions needed, confirmation prompts, error handling, or what happens if the job doesn't exist.
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?
The description is a single, efficient sentence that directly states the tool's purpose without any unnecessary words. It's appropriately sized and front-loaded with the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive operation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what happens after deletion (e.g., confirmation message, error responses), nor does it address important behavioral aspects like permissions or irreversible consequences.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the single parameter 'job_id' clearly documented. The description doesn't add any additional parameter semantics beyond what the schema already provides, so the baseline score of 3 is appropriate.
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 the specific action ('Delete') and target resource ('a voiceover job and its associated files'), making the purpose unambiguous. It distinguishes this destructive operation from sibling tools that are primarily about generation, retrieval, or listing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives or any prerequisites. While it's clear this is for deletion, there's no mention of when deletion is appropriate versus other operations like retrieving or listing jobs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves history but doesn't describe return format, pagination, error handling, authentication needs, rate limits, or whether it's read-only. The description is minimal and lacks essential behavioral context for a tool with no annotation coverage.
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?
The description is extremely concise with two sentences that are front-loaded and waste-free. The first sentence states the core purpose, and the second clarifies the optional parameter usage, making it efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a simple input schema, the description is incomplete. It doesn't explain what 'voiceover job history' entails (e.g., list of jobs, statuses, metadata), return values, or behavioral traits like safety or performance. For a tool with minimal structured data, the description should provide more context to be fully helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the parameter 'job_id' documented as 'Optional job ID to get details for a specific job'. The description adds minimal value by restating this as 'Optionally specify a job ID for a specific job', which doesn't provide additional semantics beyond the schema. Baseline 3 is appropriate given high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'Get voiceover job history' with the verb 'Get' and resource 'voiceover job history'. It distinguishes between retrieving general history versus specific job details, though it doesn't explicitly differentiate from sibling tools like 'get_audio_file' or 'list_voices'.
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?
The description provides implied usage guidance by mentioning the optional job ID parameter for retrieving a specific job, which suggests when to use this tool versus alternatives. However, it lacks explicit guidance on when to use this tool over siblings like 'get_audio_file' or 'list_voices', and no exclusions or prerequisites are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states what the tool does but doesn't describe traits like whether it's read-only (implied by 'Get'), rate limits, authentication needs, error conditions, or what 'metadata' includes. For a tool with zero annotation coverage, this leaves significant behavioral gaps.
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?
The description is a single, efficient sentence that front-loads the core purpose ('Get a list...') with no wasted words. Every part earns its place by specifying the resource and scope ('all available ElevenLabs voices with metadata').
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 the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. It explains what the tool does but lacks details on behavior, output format, or usage context. For a read operation with no structured output documentation, more completeness would help the agent understand what to expect.
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?
The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the lack of inputs. The description adds no parameter information beyond this, which is appropriate. Baseline for 0 parameters is 4, as no compensation is needed for schema gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and resource ('list of all available ElevenLabs voices with metadata'), making the purpose specific and understandable. It doesn't explicitly distinguish from sibling tools like 'get_voiceover_history' or 'get_audio_file', but the focus on voices rather than audio files or history provides implicit differentiation. A 5 would require explicit sibling comparison.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, timing considerations, or compare it to sibling tools like 'get_voiceover_history' for historical data or 'generate_audio_simple' for voice selection. The agent must infer usage from the purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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