VRChat MCP OSC
Enables AI-driven avatar control and interactions in VRChat through OSC, allowing manipulation of avatar parameters, movement control, message sending, menu toggling, and retrieval of avatar information.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@VRChat MCP OSCwave to my friend by triggering the wave emote"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
VRChat MCP OSC
VRChat MCP OSC provides a bridge between AI assistants and VRChat using the Model Context Protocol (MCP), enabling AI-driven avatar control and interactions in virtual reality environments.
Overview
By leveraging OSC (Open Sound Control) to communicate with VRChat, VRChat MCP OSC allows AI assistants such as Claude to:
Control avatar parameters and expressions
Send messages in VRChat
Respond to various VR events
And more—all through the high-level API provided by the Model Context Protocol.
Related MCP server: Blender MCP
Key Features
Avatar Control: Manipulate avatar parameters and expressions
Movement Control: Direct avatar movement and orientation
Communication: Send messages through VRChat's chatbox
Menu Access: Toggle VRChat menu and interface elements
Avatar Information: Query avatar properties and parameters
Seamless VRChat Integration: Automatic detection of avatar configurations
System Requirements
Node.js 18 or higher
VRChat with OSC enabled
Claude Desktop (with MCP support)
Using with Claude Desktop
Clone and npm link
git clone https://github.com/Krekun/vrchat-mcp-osc
cd vrchat-mcp-osc
npm linkConfigure Claude Desktop
Configure Claude Desktop by editing the claude_desktop_config.json file:
{
"mcpServers": {
"vrchat-mcp-osc": {
"command": "npx",
"args": [
"vrchat-mcp-osc"
]
}
}
}Command Line Options
The server supports various command-line arguments for customization:
# Claude Desktop configuration
{
"mcpServers": {
"vrchat-mcp-osc": {
"command": "npx",
"args": [
"vrchat-mcp-osc",
"--websocket-port", "8765",
"--websocket-host", "localhost",
"--osc-send-port", "9000",
"--osc-send-ip", "127.0.0.1",
"--osc-receive-port", "9001",
"--osc-receive-ip", "127.0.0.1",
"--debug"
]
}
}
}Available Options
Option | Description | Default | Notes |
| WebSocket port | 8765 | For WebSocket communication |
| WebSocket host | localhost | For WebSocket communication |
| OSC send port | 9000 | Port for sending to VRChat |
| OSC send IP | 127.0.0.1 | Address for sending to VRChat |
| OSC receive port | 9001 | Port for receiving from VRChat |
| OSC receive IP | 127.0.0.1 | Address for receiving from VRChat |
| Enable debug logging | false | Output detailed logs |
| Disable relay server | false | When not using relay server |
Available MCP Tools
VRChat MCP OSC exposes the following MCP tools to AI assistants:
Tool Name | Description |
| Retrieves the current avatar's name |
| Lists available avatar parameters |
| Sets a specific avatar parameter |
| Triggers avatar emotes |
| Moves the avatar in a specific direction |
| Controls avatar's view direction |
| Makes the avatar jump |
| Toggles the VRChat menu |
| Toggles voice features |
| Sends a message to the VRChat chatbox |
Troubleshooting
Common Issues
VRChat not responding to commands
Ensure OSC is enabled in VRChat settings
Check that the OSC ports match between VRChat and MCP configuration
Restart VRChat and Claude Desktop
MCP server not starting
Ensure Node.js 18+ is installed
Check command line arguments for errors
Try running with
--debugflag for more detailed logsUse
npx vrchat-mcp-osc -- --debugif direct arguments don't work
NPX execution issues
If arguments aren't being recognized, try using the double dash format:
npx vrchat-mcp-osc -- --debugOn Windows, try running in a command prompt with administrator privileges
If you're having trouble with global installation, try the local npm link approach
Project Structure
vrchat-mcp-osc/
├── packages/
│ ├── mcp-server/ # MCP server implementation (main entry point)
│ ├── relay-server/ # WebSocket to OSC relay
│ ├── types/ # Shared TypeScript interfaces
│ └── utils/ # Common utilities
└── pnpm-workspace.yaml # Workspace configurationDevelopment
Build From Source
# Clone the repository
git clone https://github.com/Krekun/vrchat-mcp-osc
cd vrchat-mcp-osc
# Install dependencies
pnpm install
# Build all packages
pnpm -r build
# Development mode
pnpm -r devLicense
VRChat MCP OSC is dual-licensed as follows:
For Non-Commercial Use: You may use, modify, and redistribute the software under the terms of the MIT License. (See the MIT License file for details.)
For Commercial Use: Commercial use of this software requires a separate commercial license.
By using this software under the MIT License for non-commercial purposes, you agree to the terms of that license. Commercial users must obtain a commercial license as described above.
Acknowledgments
VRChat team for the OSC integration
Model Context Protocol for the standardized AI interface
Anthropic for Claude's MCP implementation
Available Tools
12 toolsget_avatar_listB
Get a list of available avatars.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
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 retrieves a list but doesn't describe what 'available avatars' means (e.g., user-owned, system-default, or all), whether it requires authentication, rate limits, or the format of the returned list. This leaves significant gaps for a tool with zero 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with zero wasted words. It's front-loaded with the core action ('Get a list') and resource ('available avatars'), making it highly efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the list contains (e.g., avatar IDs, names, images), how it's structured, or any prerequisites for use. For a tool with no structured data to rely on, this leaves too much undefined for effective agent operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, but this is appropriate given the schema's completeness. A baseline of 4 is applied as it adequately handles the lack of parameters without introducing confusion.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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 available avatars'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'get_avatar_name' or 'get_avatar_parameters', but the focus on listing all avatars is specific enough for basic clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 like 'get_avatar_name' (which might retrieve details for a specific avatar) or 'set_avatar' (which modifies avatars). It lacks explicit when/when-not instructions or named alternatives, leaving usage context implied at best.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_avatar_nameB
Get the name of the current avatar.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
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 but only states the basic action. It doesn't reveal any behavioral traits such as whether this is a read-only operation, if it requires authentication, potential rate limits, or what the return format might be (e.g., string, object). This leaves significant gaps in understanding how the tool behaves in practice.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that directly states the tool's purpose without any unnecessary words or fluff. It is front-loaded and efficiently communicates the core functionality, making it easy for an agent to parse and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete for effective tool use. It doesn't explain what the tool returns (e.g., a string name, an error if no avatar exists), behavioral aspects like safety or side effects, or how it fits with sibling tools. For a tool in a server with multiple avatar-related tools, more context is needed to ensure proper selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and the input schema coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, and it correctly avoids mentioning any inputs. This meets the baseline expectation for a parameterless tool, though it doesn't go beyond that.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get') and resource ('name of the current avatar'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_avatar_list' or 'set_avatar', which also deal with avatars, leaving room for potential confusion about when to use this specific tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 any context, prerequisites, or exclusions, nor does it refer to sibling tools like 'get_avatar_list' for listing avatars or 'set_avatar' for modifying them, leaving the agent to infer usage scenarios independently.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_avatar_parametersB
Get a list of parameters available on the current avatar.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
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 this is a 'Get' operation (implying read-only) but doesn't mention permissions, rate limits, error conditions, or what format the returned list has. For a tool with zero annotation coverage, this is insufficient behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 appropriately sized for a simple tool and front-loads the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters, no annotations, and no output schema, the description provides the basic purpose but lacks important context about what the returned list contains, how it's structured, or any behavioral constraints. For a read operation that returns data, more detail about the output would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 already fully documents the lack of parameters. The description appropriately doesn't add parameter information beyond what's in the schema, maintaining a baseline score of 4 for zero-parameter tools.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get a list') and resource ('parameters available on the current avatar'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'get_avatar_list' or 'set_avatar_parameter', which would be needed for a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 like 'get_avatar_list' or 'set_avatar_parameter'. It mentions 'current avatar' but doesn't explain prerequisites or context for when this tool is appropriate versus other avatar-related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
jumpB
Make the avatar jump.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
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. While 'Make the avatar jump' implies an action, it doesn't describe what 'jump' means in this context, whether it's instantaneous or has duration, what visual/audio effects occur, or whether it affects other avatar parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is maximally concise at just three words, front-loading the essential action without any wasted words. Every element ('Make', 'the avatar', 'jump') earns its place in conveying the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter action tool with no annotations and no output schema, the description provides the basic action but lacks context about what 'jump' entails behaviorally. It's adequate as a minimum viable description but has clear gaps in explaining the tool's effects and behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 baseline is 4. The description appropriately doesn't discuss parameters since none exist, and the schema already fully documents the empty parameter set.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Make') and the target ('the avatar jump'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'move_avatar' or 'set_avatar_parameter' that might involve avatar movement or state changes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives. There's no mention of prerequisites, timing considerations, or how it differs from similar sibling tools like 'move_avatar' or 'set_avatar_parameter'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
look_directionC
Turn to look in a specific direction.
| Name | Required | Description | Default |
|---|---|---|---|
| direction | Yes | Direction to look | |
| duration | No | Duration in seconds |
TDQS
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 the action but lacks critical details: whether this requires specific permissions (e.g., avatar control), if it's reversible, what happens if duration is zero/negative, or what visual/state changes occur. For a mutation tool with zero annotation coverage, this is inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core action ('Turn to look') and specifies the scope ('in a specific direction'), making it immediately understandable without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a mutation tool (implied by 'Turn') with no annotations and no output schema, the description is insufficient. It doesn't explain what 'looking' entails (e.g., camera rotation, avatar head turn), success/failure conditions, or return values, leaving significant gaps for agent understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with clear parameter documentation in the schema itself. The description adds no additional meaning about parameters beyond implying directionality, so it meets the baseline of 3 where the schema does the heavy lifting without compensating for gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Turn to look') and specifies the target ('in a specific direction'), making the purpose immediately understandable. However, it doesn't differentiate this tool from potential sibling actions like 'move_avatar' or 'set_avatar_parameter' that might also involve orientation changes, preventing a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 like 'set_avatar_parameter' for orientation or 'move_avatar' for directional movement. There's no mention of prerequisites, context (e.g., avatar must be controllable), or exclusions, leaving usage entirely implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
move_avatarC
Move the avatar in a specific direction.
| Name | Required | Description | Default |
|---|---|---|---|
| direction | Yes | Direction to move | |
| duration | No | Duration in seconds |
TDQS
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 is to move the avatar, implying a mutation, but doesn't cover aspects like whether this requires specific permissions, if it's reversible, what happens on collision, or any rate limits. This leaves significant gaps for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words, making it highly efficient and easy to parse. It's appropriately sized for the tool's apparent simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns, potential side effects, or error conditions, leaving the agent with insufficient information for reliable invocation in a complex environment.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% description coverage, fully documenting both parameters (direction with enum values and duration with default). The description adds no additional meaning beyond implying direction is involved, so it meets the baseline of 3 without compensating for any schema gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Move') and the resource ('the avatar'), specifying it's in a direction. However, it doesn't distinguish this from sibling tools like 'jump' or 'look_direction', which might involve similar movement concepts, leaving some ambiguity about unique functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 like 'jump' or 'set_avatar_parameter', nor does it mention any prerequisites or exclusions. This lack of context makes it hard for an agent to choose appropriately among similar tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
send_messageB
Send a message to the VRChat chatbox.
| Name | Required | Description | Default |
|---|---|---|---|
| message | Yes | Message to send | |
| send_immediately | No | Send immediately or just populate chatbox |
TDQS
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. While 'Send a message' implies a write operation, the description lacks details on permissions, rate limits, side effects (e.g., chat visibility), or response behavior. The mention of 'chatbox' adds some context, but overall behavioral traits are minimally covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 is appropriately sized and front-loaded, making it easy to understand quickly with zero waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (a write operation with two parameters), lack of annotations, and no output schema, the description is minimally adequate. It covers the basic action but lacks depth on behavioral aspects and output expectations, making it complete enough for a simple tool but with clear gaps for informed usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 ('message' and 'send_immediately') with clear descriptions. The tool description adds no additional parameter semantics beyond what the schema provides, adhering to the baseline score when schema coverage is high.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Send a message') and the target ('to the VRChat chatbox'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from potential alternatives or siblings, as none of the listed sibling tools appear to handle chat functionality directly, so differentiation isn't explicitly needed but could be implied by context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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, prerequisites, or contextual constraints. It simply states what the tool does without indicating appropriate scenarios or exclusions, leaving usage entirely to inference from the tool name and basic functionality.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
set_avatarC
Change to a specific avatar.
| Name | Required | Description | Default |
|---|---|---|---|
| avatar_id | Yes | ID of the avatar to change to |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. 'Change to a specific avatar' implies a mutation but does not disclose behavioral traits such as permissions required, whether the change is reversible, effects on other avatar states, or error handling. This is inadequate for a mutation tool with zero 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It is front-loaded and directly states the tool's purpose, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a mutation with no annotations and no output schema), the description is insufficient. It lacks details on behavioral aspects, usage context, and expected outcomes, failing to compensate for the absence of structured data. This leaves significant gaps for an agent to understand and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'avatar_id' documented as 'ID of the avatar to change to'. The description adds no additional meaning beyond this, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate as the schema handles parameter documentation adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Change to a specific avatar' clearly states the action (change) and resource (avatar), distinguishing it from sibling tools like get_avatar_list (list) or move_avatar (move). However, it lacks specificity about what 'change' entails compared to set_avatar_parameter, which might adjust avatar attributes rather than switching avatars entirely.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 does not mention prerequisites (e.g., needing an avatar list first), exclusions, or comparisons to siblings like set_avatar_parameter or move_avatar, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
set_avatar_parameterC
Set a parameter on the current avatar.
| Name | Required | Description | Default |
|---|---|---|---|
| parameter_name | Yes | Name of the parameter to set | |
| value | Yes | Value to set |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states the action without disclosing behavioral traits. It doesn't mention if this requires specific permissions, whether changes are reversible, what happens to other parameters, or any rate limits. The description is minimal and lacks critical context for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's front-loaded and appropriately sized for the tool's apparent simplicity, though this conciseness comes at the cost of completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's mutation nature, lack of annotations, and no output schema, the description is incomplete. It doesn't explain what parameters are available, what the value types correspond to, or what the tool returns, leaving significant gaps for an agent to operate safely and effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents both parameters (parameter_name and value). The description adds no additional meaning beyond implying these parameters exist, meeting the baseline for high schema coverage without compensating with extra details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Set a parameter on the current avatar' clearly states the action (set) and target (parameter on avatar), but it's vague about what parameters exist or what this affects. It distinguishes from siblings like 'get_avatar_parameters' (read vs. write) but doesn't specify scope beyond 'current avatar'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'set_avatar' or 'set_emote_parameter'. It implies usage for parameter modification but doesn't mention prerequisites, side effects, or contextual constraints, leaving the agent to guess based on sibling names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
set_emote_parameterC
Set VRCEmote on the current avatar.
| Name | Required | Description | Default |
|---|---|---|---|
| value | Yes | Value to set |
TDQS
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 sets a parameter, implying a mutation, but doesn't describe effects (e.g., whether it changes avatar state immediately, requires specific conditions, or has side effects). This leaves significant gaps for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words, clearly front-loading the core action. It's appropriately sized for a simple tool with one parameter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., what 'Set' entails, error conditions, or return values), making it inadequate for safe and effective use by an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the parameter 'value' documented as a number or string. The description adds no additional meaning beyond implying it's for 'VRCEmote', which loosely relates to the parameter but doesn't specify valid values or formats. Baseline 3 is appropriate given the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Set') and the target ('VRCEmote on the current avatar'), making the purpose understandable. It doesn't explicitly differentiate from sibling tools like 'set_avatar_parameter', but the specific mention of 'VRCEmote' provides some distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'set_avatar_parameter' or other avatar-related tools. The description implies usage for setting emote parameters but offers no context about prerequisites, timing, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
voiceC
Toggle voice
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
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. 'Toggle voice' implies a mutation action (changing state), but it doesn't specify what the toggle does (e.g., enable/disable voice, switch between voice modes), what the default state is, or any side effects like requiring permissions or affecting other tools. This leaves critical behavioral traits unclear for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description 'Toggle voice' is extremely concise at two words, which could be seen as efficient. However, it's arguably under-specified rather than appropriately concise, as it lacks necessary context for a mutation tool. It's front-loaded but doesn't earn its place with sufficient information, making it borderline between concise and inadequate.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity as a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'voice' refers to, what toggling entails, or what the expected outcome is. For a tool that likely changes system state, this minimal description fails to provide enough context for safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate here. A baseline of 4 is assigned because the schema fully handles the parameter semantics, and the description doesn't need to compensate for any gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Toggle voice' is a tautology that essentially restates the tool name 'voice' with minimal elaboration. While it indicates an action ('toggle'), it doesn't specify what resource or system component is being toggled (e.g., voice chat, voice input, voice output), nor does it distinguish this tool from siblings like 'set_avatar_parameter' or 'set_emote_parameter' that might involve voice-related settings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 any context, prerequisites, or exclusions, such as whether it requires specific avatar settings or if it's only applicable in certain modes. Given siblings like 'set_avatar_parameter' that might control voice parameters, this lack of differentiation is a significant gap.
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.
12 tool updates
v1.0.0- First observed
get_avatar_list - First observed
get_avatar_name - First observed
get_avatar_parameters - First observed
jump - First observed
look_direction - First observed
menu - First observed
move_avatar - First observed
send_message - First observed
set_avatar - First observed
set_avatar_parameter - First observed
set_emote_parameter - First observed
voice
TDQS
Most tools have distinct purposes, but there is some potential overlap between 'move_avatar' and 'look_direction' for avatar movement/positioning, and 'set_avatar_parameter' and 'set_emote_parameter' both involve parameter setting. The descriptions help clarify differences, but an agent might occasionally confuse these pairs.
The naming follows a consistent verb_noun pattern (e.g., get_avatar_list, set_avatar_parameter) with minor deviations like 'jump' and 'voice' being single words instead of verb_noun pairs. Overall, it's readable and mostly predictable, though not perfectly uniform.
With 12 tools, this is well-scoped for controlling VRChat avatars via OSC. Each tool serves a clear purpose, such as avatar management, movement, communication, and parameter control, without feeling excessive or insufficient for the domain.
The toolset covers key aspects like avatar selection, movement, communication, and parameter control, but there are minor gaps such as missing tools for advanced interactions (e.g., gesture controls or environment manipulation). However, agents can likely work around these with the provided tools.
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