post_dataforseo_ai_gemini_llm_responses_live Live Gemini LLM Responses endpoint allows you to retrieve structured responses from a specific Gemini AI model, based on the input parameters.
Usage-based billing; Default request estimate: $0.0707 USD (not a fixed price). Account-specific pricing and final settlement may differ.
| Name | Required | Description | Default |
|---|---|---|---|
| body | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Input schema / properties / body / items / oneOfPrevious value: -[
- {
- "example": [
- {
- "max_output_tokens": 200,
- "message_chain": [
- {
- "message": "Hello, what’s up?",
- "role": "user"
- },
- {
- "message": "Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?",
- "role": "ai"
- }
- ],
- "model_name": "gemini-2.5-flash",
- "system_message": "communicate as if we are in a business meeting",
- "temperature": 0.3,
- "top_p": 0.5,
- "user_prompt": "provide information on how relevant the amusement park business is in France now",
- "web_search": true
- }
- ],
- "properties": {
- "max_output_tokens": {
- "description": "<em>maximum number of tokens in the AI response</em><br>optional field<br>minimum value: <code>1</code><br>maximum value: <code>4096</code>;<br>default value: <code>2048</code>;<br><strong>Note:</strong> if <code>web_search</code> is set to <code>true</code> or the reasoning model is specified in the request, the output token count may exceed the specified <code>max_output_tokens</code> limit<br><strong>Note #2:</strong> if <code>use_reasoning</code> is set to <code>true</code>, the minimum value for <code>max_output_tokens</code> is <code>1024</code>",
- "type": [
- "integer",
- "null"
- ]
- },
- "message_chain": {
- "description": "conversation history\noptional field\narray of message objects representing previous conversation turns;\neach object must contain:\nrole string with either user or ai role;\nmessage string with message content (max 500 characters);\nyou can specify maximum of 10 message objects in the array;\nNote: for Perplexity models, messages must strictly alternate between user and AI roles (user → ai);\nexample:\n\"message_chain\": [{\"role\":\"user\",\"message\":\"Hello, what’s up?\"},{\"role\":\"ai\",\"message\":\"Hello! I’m doing well, thank you. How can I assist you today?\"}]",
- "items": {
- "oneOf": [
- {
- "properties": {
- "message": {
- "description": "message text",
- "type": [
- "string",
- "null"
- ]
- },
- "role": {
- "description": "role of the user from whom the message originates",
- "type": [
- "string",
- "null"
- ]
- }
- },
- "type": "object"
- }
- ],
- "type": [
- "object",
- "null"
- ]
- },
- "type": [
- "array",
- "null"
- ]
- },
- "model_name": {
- "description": "<em>name of the AI model</em><br><strong>required field</strong><br><code>model_name</code >consists of the actual model name and version name;<br>if the basic model name is specified, its latest version will be set by default;<br>for example, if <code>gemini-1.5-pro</code> is specified, the <code>gemini-1.5-pro-002</code> will be set as <code>model_name</code> automatically;<br>you can receive the list of available LLM models by making a separate request to the <code>https://api.dataforseo.com/v3/ai_optimization/gemini/llm_responses/models</code>",
- "type": "string"
- },
- "system_message": {
- "description": "<em>instructions for the AI behavior</em><br>optional field<br>defines the AI's role, tone, or specific behavior <br>you can specify <strong>up to 500 characters</strong> in the <code>system_message</code> field",
- "type": [
- "string",
- "null"
- ]
- },
- "tag": {
- "description": "<em>user-defined task identifier</em><br>optional field<br><em>the character limit is 255</em><br>you can use this parameter to identify the task and match it with the result<br>you will find the specified <code>tag</code> value in the <code>data</code> object of the response",
- "type": [
- "string",
- "null"
- ]
- },
- "temperature": {
- "description": "<em>randomness of the AI response</em><br>optional field<br>higher values make output more diverse <br>lower values make output more focused<br>minimum value: <code>0</code><br>maximum value: <code>2</code><br>default value: <code>1.3</code>",
- "type": [
- "number",
- "null"
- ]
- },
- "top_p": {
- "description": "<em>diversity of the AI response</em><br>optional field <br>controls diversity of the response by limiting token selection<br>minimum value: <code>0</code><br>maximum value: <code>1</code> <br>default value: <code>0.9</code>",
- "type": [
- "number",
- "null"
- ]
- },
- "use_reasoning": {
- "description": "<em>enable reasoning for the AI model</em><br>optional field<br>when enabled, the model will perform reasoning before generating a response<br>refer to the <a href=\"https://docs.dataforseo.com/v3/ai_optimization/gemini/llm_responses/models/\" target=\"_blank\">Models endpoint</a> for a list of models that support <code>reasoning</code><br>default value: <code>false</code><br><strong>Note:</strong> if set to <code>true</code>, the minimum value for <code>max_output_tokens</code> is <code>1024</code><br><strong>Note #2:</strong> for Gemini Pro models, the <code>use_reasoning</code> will automatically be set to <code>true</code>",
- "type": [
- "boolean",
- "null"
- ]
- },
- "user_prompt": {
- "description": "<em>prompt for the AI model</em><br><strong>required field</strong><br>the question or task you want to send to the AI model;<br>you can specify <strong>up to 500 characters</strong> in the <code>user_prompt</code> field",
- "type": "string"
- },
- "web_search": {
- "description": "<em>enable web search for current information</em><br>optional field<br>when enabled, the AI model can access and cite current web information;<br><strong>Note:</strong> refer to the <a href=\"https://docs.dataforseo.com/v3/ai_optimization/gemini/llm_responses/models/\">Models endpoint</a> for a list of models that support <code>web_search</code>; <br>default value: <code>false</code>;<br>The cost of the parameter can be calculated on the <a title=\"Gemini API Pricing\" href=\"https://ai.google.dev/gemini-api/docs/pricing\" target=\"_blank\" rel=\"noopener noreferrer\">Pricing</a> page",
- "type": [
- "boolean",
- "null"
- ]
- }
- },
- "type": "object"
- }
-]New value: +[
+ {
+ "properties": {
+ "max_output_tokens": {
+ "description": "<em>maximum number of tokens in the AI response</em><br>optional field<br>minimum value: <code>1</code><br>maximum value: <code>4096</code>;<br>default value: <code>2048</code>;<br><strong>Note:</strong> if <code>web_search</code> is set to <code>true</code> or the reasoning model is specified in the request, the output token count may exceed the specified <code>max_output_tokens</code> limit<br><strong>Note #2:</strong> if <code>use_reasoning</code> is set to <code>true</code>, the minimum value for <code>max_output_tokens</code> is <code>1024</code>",
+ "type": [
+ "integer",
+ "null"
+ ]
+ },
+ "message_chain": {
+ "description": "conversation history\noptional field\narray of message objects representing previous conversation turns;\neach object must contain:\nrole string with either user or ai role;\nmessage string with message content (max 500 characters);\nyou can specify maximum of 10 message objects in the array;\nNote: for Perplexity models, messages must strictly alternate between user and AI roles (user → ai);\nexample:\n\"message_chain\": [{\"role\":\"user\",\"message\":\"Hello, what’s up?\"},{\"role\":\"ai\",\"message\":\"Hello! I’m doing well, thank you. How can I assist you today?\"}]",
+ "items": {
+ "oneOf": [
+ {
+ "properties": {
+ "message": {
+ "description": "message text",
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "role": {
+ "description": "role of the user from whom the message originates",
+ "type": [
+ "string",
+ "null"
+ ]
+ }
+ },
+ "type": "object"
+ }
+ ],
+ "type": [
+ "object",
+ "null"
+ ]
+ },
+ "type": [
+ "array",
+ "null"
+ ]
+ },
+ "model_name": {
+ "description": "<em>name of the AI model</em><br><strong>required field</strong><br><code>model_name</code >consists of the actual model name and version name;<br>if the basic model name is specified, its latest version will be set by default;<br>for example, if <code>gemini-1.5-pro</code> is specified, the <code>gemini-1.5-pro-002</code> will be set as <code>model_name</code> automatically;<br>you can receive the list of available LLM models by making a separate request to the <code>https://api.dataforseo.com/v3/ai_optimization/gemini/llm_responses/models</code>",
+ "type": "string"
+ },
+ "system_message": {
+ "description": "<em>instructions for the AI behavior</em><br>optional field<br>defines the AI's role, tone, or specific behavior <br>you can specify <strong>up to 500 characters</strong> in the <code>system_message</code> field",
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "tag": {
+ "description": "<em>user-defined task identifier</em><br>optional field<br><em>the character limit is 255</em><br>you can use this parameter to identify the task and match it with the result<br>you will find the specified <code>tag</code> value in the <code>data</code> object of the response",
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "temperature": {
+ "description": "<em>randomness of the AI response</em><br>optional field<br>higher values make output more diverse <br>lower values make output more focused<br>minimum value: <code>0</code><br>maximum value: <code>2</code><br>default value: <code>1.3</code>",
+ "type": [
+ "number",
+ "null"
+ ]
+ },
+ "top_p": {
+ "description": "<em>diversity of the AI response</em><br>optional field <br>controls diversity of the response by limiting token selection<br>minimum value: <code>0</code><br>maximum value: <code>1</code> <br>default value: <code>0.9</code>",
+ "type": [
+ "number",
+ "null"
+ ]
+ },
+ "use_reasoning": {
+ "description": "<em>enable reasoning for the AI model</em><br>optional field<br>when enabled, the model will perform reasoning before generating a response<br>refer to the <a href=\"https://docs.dataforseo.com/v3/ai_optimization/gemini/llm_responses/models/\" target=\"_blank\">Models endpoint</a> for a list of models that support <code>reasoning</code><br>default value: <code>false</code><br><strong>Note:</strong> if set to <code>true</code>, the minimum value for <code>max_output_tokens</code> is <code>1024</code><br><strong>Note #2:</strong> for Gemini Pro models, the <code>use_reasoning</code> will automatically be set to <code>true</code>",
+ "type": [
+ "boolean",
+ "null"
+ ]
+ },
+ "user_prompt": {
+ "description": "<em>prompt for the AI model</em><br><strong>required field</strong><br>the question or task you want to send to the AI model;<br>you can specify <strong>up to 500 characters</strong> in the <code>user_prompt</code> field",
+ "type": "string"
+ },
+ "web_search": {
+ "description": "<em>enable web search for current information</em><br>optional field<br>when enabled, the AI model can access and cite current web information;<br><strong>Note:</strong> refer to the <a href=\"https://docs.dataforseo.com/v3/ai_optimization/gemini/llm_responses/models/\">Models endpoint</a> for a list of models that support <code>web_search</code>; <br>default value: <code>false</code>;<br>The cost of the parameter can be calculated on the <a title=\"Gemini API Pricing\" href=\"https://ai.google.dev/gemini-api/docs/pricing\" target=\"_blank\" rel=\"noopener noreferrer\">Pricing</a> page",
+ "type": [
+ "boolean",
+ "null"
+ ]
+ }
+ },
+ "type": "object"
+ }
+]Input schema / properties / body / items / anyOfRemoved value: -[
- {
- "example": [
- {
- "max_output_tokens": 200,
- "message_chain": [
- {
- "message": "Hello, what’s up?",
- "role": "user"
- },
- {
- "message": "Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?",
- "role": "ai"
- }
- ],
- "model_name": "gemini-2.5-flash",
- "system_message": "communicate as if we are in a business meeting",
- "temperature": 0.3,
- "top_p": 0.5,
- "user_prompt": "provide information on how relevant the amusement park business is in France now",
- "web_search": true
- }
- ],
- "properties": {
- "max_output_tokens": {
- "description": "<em>maximum number of tokens in the AI response</em><br>optional field<br>minimum value: <code>1</code><br>maximum value: <code>4096</code>;<br>default value: <code>2048</code>;<br><strong>Note:</strong> if <code>web_search</code> is set to <code>true</code> or the reasoning model is specified in the request, the output token count may exceed the specified <code>max_output_tokens</code> limit<br><strong>Note #2:</strong> if <code>use_reasoning</code> is set to <code>true</code>, the minimum value for <code>max_output_tokens</code> is <code>1024</code>",
- "type": [
- "integer",
- "null"
- ]
- },
- "message_chain": {
- "description": "conversation history\noptional field\narray of message objects representing previous conversation turns;\neach object must contain:\nrole string with either user or ai role;\nmessage string with message content (max 500 characters);\nyou can specify maximum of 10 message objects in the array;\nNote: for Perplexity models, messages must strictly alternate between user and AI roles (user → ai);\nexample:\n\"message_chain\": [{\"role\":\"user\",\"message\":\"Hello, what’s up?\"},{\"role\":\"ai\",\"message\":\"Hello! I’m doing well, thank you. How can I assist you today?\"}]",
- "items": {
- "anyOf": [
- {
- "properties": {
- "message": {
- "description": "message text",
- "type": [
- "string",
- "null"
- ]
- },
- "role": {
- "description": "role of the user from whom the message originates",
- "type": [
- "string",
- "null"
- ]
- }
- },
- "type": "object"
- }
- ],
- "type": [
- "object",
- "null"
- ]
- },
- "type": [
- "array",
- "null"
- ]
- },
- "model_name": {
- "description": "<em>name of the AI model</em><br><strong>required field</strong><br><code>model_name</code >consists of the actual model name and version name;<br>if the basic model name is specified, its latest version will be set by default;<br>for example, if <code>gemini-1.5-pro</code> is specified, the <code>gemini-1.5-pro-002</code> will be set as <code>model_name</code> automatically;<br>you can receive the list of available LLM models by making a separate request to the <code>https://api.dataforseo.com/v3/ai_optimization/gemini/llm_responses/models</code>",
- "type": "string"
- },
- "system_message": {
- "description": "<em>instructions for the AI behavior</em><br>optional field<br>defines the AI's role, tone, or specific behavior <br>you can specify <strong>up to 500 characters</strong> in the <code>system_message</code> field",
- "type": [
- "string",
- "null"
- ]
- },
- "tag": {
- "description": "<em>user-defined task identifier</em><br>optional field<br><em>the character limit is 255</em><br>you can use this parameter to identify the task and match it with the result<br>you will find the specified <code>tag</code> value in the <code>data</code> object of the response",
- "type": [
- "string",
- "null"
- ]
- },
- "temperature": {
- "description": "<em>randomness of the AI response</em><br>optional field<br>higher values make output more diverse <br>lower values make output more focused<br>minimum value: <code>0</code><br>maximum value: <code>2</code><br>default value: <code>1.3</code>",
- "type": [
- "number",
- "null"
- ]
- },
- "top_p": {
- "description": "<em>diversity of the AI response</em><br>optional field <br>controls diversity of the response by limiting token selection<br>minimum value: <code>0</code><br>maximum value: <code>1</code> <br>default value: <code>0.9</code>",
- "type": [
- "number",
- "null"
- ]
- },
- "use_reasoning": {
- "description": "<em>enable reasoning for the AI model</em><br>optional field<br>when enabled, the model will perform reasoning before generating a response<br>refer to the <a href=\"https://docs.dataforseo.com/v3/ai_optimization/gemini/llm_responses/models/\" target=\"_blank\">Models endpoint</a> for a list of models that support <code>reasoning</code><br>default value: <code>false</code><br><strong>Note:</strong> if set to <code>true</code>, the minimum value for <code>max_output_tokens</code> is <code>1024</code><br><strong>Note #2:</strong> for Gemini Pro models, the <code>use_reasoning</code> will automatically be set to <code>true</code>",
- "type": [
- "boolean",
- "null"
- ]
- },
- "user_prompt": {
- "description": "<em>prompt for the AI model</em><br><strong>required field</strong><br>the question or task you want to send to the AI model;<br>you can specify <strong>up to 500 characters</strong> in the <code>user_prompt</code> field",
- "type": "string"
- },
- "web_search": {
- "description": "<em>enable web search for current information</em><br>optional field<br>when enabled, the AI model can access and cite current web information;<br><strong>Note:</strong> refer to the <a href=\"https://docs.dataforseo.com/v3/ai_optimization/gemini/llm_responses/models/\">Models endpoint</a> for a list of models that support <code>web_search</code>; <br>default value: <code>false</code>;<br>The cost of the parameter can be calculated on the <a title=\"Gemini API Pricing\" href=\"https://ai.google.dev/gemini-api/docs/pricing\" target=\"_blank\" rel=\"noopener noreferrer\">Pricing</a> page",
- "type": [
- "boolean",
- "null"
- ]
- }
- },
- "type": "object"
- }
-]Input schema / properties / body / items / oneOfAdded value: +[
+ {
+ "example": [
+ {
+ "max_output_tokens": 200,
+ "message_chain": [
+ {
+ "message": "Hello, what’s up?",
+ "role": "user"
+ },
+ {
+ "message": "Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?",
+ "role": "ai"
+ }
+ ],
+ "model_name": "gemini-2.5-flash",
+ "system_message": "communicate as if we are in a business meeting",
+ "temperature": 0.3,
+ "top_p": 0.5,
+ "user_prompt": "provide information on how relevant the amusement park business is in France now",
+ "web_search": true
+ }
+ ],
+ "properties": {
+ "max_output_tokens": {
+ "description": "<em>maximum number of tokens in the AI response</em><br>optional field<br>minimum value: <code>1</code><br>maximum value: <code>4096</code>;<br>default value: <code>2048</code>;<br><strong>Note:</strong> if <code>web_search</code> is set to <code>true</code> or the reasoning model is specified in the request, the output token count may exceed the specified <code>max_output_tokens</code> limit<br><strong>Note #2:</strong> if <code>use_reasoning</code> is set to <code>true</code>, the minimum value for <code>max_output_tokens</code> is <code>1024</code>",
+ "type": [
+ "integer",
+ "null"
+ ]
+ },
+ "message_chain": {
+ "description": "conversation history\noptional field\narray of message objects representing previous conversation turns;\neach object must contain:\nrole string with either user or ai role;\nmessage string with message content (max 500 characters);\nyou can specify maximum of 10 message objects in the array;\nNote: for Perplexity models, messages must strictly alternate between user and AI roles (user → ai);\nexample:\n\"message_chain\": [{\"role\":\"user\",\"message\":\"Hello, what’s up?\"},{\"role\":\"ai\",\"message\":\"Hello! I’m doing well, thank you. How can I assist you today?\"}]",
+ "items": {
+ "oneOf": [
+ {
+ "properties": {
+ "message": {
+ "description": "message text",
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "role": {
+ "description": "role of the user from whom the message originates",
+ "type": [
+ "string",
+ "null"
+ ]
+ }
+ },
+ "type": "object"
+ }
+ ],
+ "type": [
+ "object",
+ "null"
+ ]
+ },
+ "type": [
+ "array",
+ "null"
+ ]
+ },
+ "model_name": {
+ "description": "<em>name of the AI model</em><br><strong>required field</strong><br><code>model_name</code >consists of the actual model name and version name;<br>if the basic model name is specified, its latest version will be set by default;<br>for example, if <code>gemini-1.5-pro</code> is specified, the <code>gemini-1.5-pro-002</code> will be set as <code>model_name</code> automatically;<br>you can receive the list of available LLM models by making a separate request to the <code>https://api.dataforseo.com/v3/ai_optimization/gemini/llm_responses/models</code>",
+ "type": "string"
+ },
+ "system_message": {
+ "description": "<em>instructions for the AI behavior</em><br>optional field<br>defines the AI's role, tone, or specific behavior <br>you can specify <strong>up to 500 characters</strong> in the <code>system_message</code> field",
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "tag": {
+ "description": "<em>user-defined task identifier</em><br>optional field<br><em>the character limit is 255</em><br>you can use this parameter to identify the task and match it with the result<br>you will find the specified <code>tag</code> value in the <code>data</code> object of the response",
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "temperature": {
+ "description": "<em>randomness of the AI response</em><br>optional field<br>higher values make output more diverse <br>lower values make output more focused<br>minimum value: <code>0</code><br>maximum value: <code>2</code><br>default value: <code>1.3</code>",
+ "type": [
+ "number",
+ "null"
+ ]
+ },
+ "top_p": {
+ "description": "<em>diversity of the AI response</em><br>optional field <br>controls diversity of the response by limiting token selection<br>minimum value: <code>0</code><br>maximum value: <code>1</code> <br>default value: <code>0.9</code>",
+ "type": [
+ "number",
+ "null"
+ ]
+ },
+ "use_reasoning": {
+ "description": "<em>enable reasoning for the AI model</em><br>optional field<br>when enabled, the model will perform reasoning before generating a response<br>refer to the <a href=\"https://docs.dataforseo.com/v3/ai_optimization/gemini/llm_responses/models/\" target=\"_blank\">Models endpoint</a> for a list of models that support <code>reasoning</code><br>default value: <code>false</code><br><strong>Note:</strong> if set to <code>true</code>, the minimum value for <code>max_output_tokens</code> is <code>1024</code><br><strong>Note #2:</strong> for Gemini Pro models, the <code>use_reasoning</code> will automatically be set to <code>true</code>",
+ "type": [
+ "boolean",
+ "null"
+ ]
+ },
+ "user_prompt": {
+ "description": "<em>prompt for the AI model</em><br><strong>required field</strong><br>the question or task you want to send to the AI model;<br>you can specify <strong>up to 500 characters</strong> in the <code>user_prompt</code> field",
+ "type": "string"
+ },
+ "web_search": {
+ "description": "<em>enable web search for current information</em><br>optional field<br>when enabled, the AI model can access and cite current web information;<br><strong>Note:</strong> refer to the <a href=\"https://docs.dataforseo.com/v3/ai_optimization/gemini/llm_responses/models/\">Models endpoint</a> for a list of models that support <code>web_search</code>; <br>default value: <code>false</code>;<br>The cost of the parameter can be calculated on the <a title=\"Gemini API Pricing\" href=\"https://ai.google.dev/gemini-api/docs/pricing\" target=\"_blank\" rel=\"noopener noreferrer\">Pricing</a> page",
+ "type": [
+ "boolean",
+ "null"
+ ]
+ }
+ },
+ "type": "object"
+ }
+]Input schema / properties / body / exampleAdded value: +[
+ {
+ "max_output_tokens": 200,
+ "message_chain": [
+ {
+ "message": "Hello, what’s up?",
+ "role": "user"
+ },
+ {
+ "message": "Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?",
+ "role": "ai"
+ }
+ ],
+ "model_name": "gemini-2.5-flash",
+ "system_message": "communicate as if we are in a business meeting",
+ "temperature": 0.3,
+ "top_p": 0.5,
+ "user_prompt": "provide information on how relevant the amusement park business is in France now",
+ "web_search": true
+ }
+]Input schema / properties / body / items / anyOfAdded value: +[
+ {
+ "example": [
+ {
+ "max_output_tokens": 200,
+ "message_chain": [
+ {
+ "message": "Hello, what’s up?",
+ "role": "user"
+ },
+ {
+ "message": "Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?",
+ "role": "ai"
+ }
+ ],
+ "model_name": "gemini-2.5-flash",
+ "system_message": "communicate as if we are in a business meeting",
+ "temperature": 0.3,
+ "top_p": 0.5,
+ "user_prompt": "provide information on how relevant the amusement park business is in France now",
+ "web_search": true
+ }
+ ],
+ "properties": {
+ "max_output_tokens": {
+ "description": "<em>maximum number of tokens in the AI response</em><br>optional field<br>minimum value: <code>1</code><br>maximum value: <code>4096</code>;<br>default value: <code>2048</code>;<br><strong>Note:</strong> if <code>web_search</code> is set to <code>true</code> or the reasoning model is specified in the request, the output token count may exceed the specified <code>max_output_tokens</code> limit<br><strong>Note #2:</strong> if <code>use_reasoning</code> is set to <code>true</code>, the minimum value for <code>max_output_tokens</code> is <code>1024</code>",
+ "type": [
+ "integer",
+ "null"
+ ]
+ },
+ "message_chain": {
+ "description": "conversation history\noptional field\narray of message objects representing previous conversation turns;\neach object must contain:\nrole string with either user or ai role;\nmessage string with message content (max 500 characters);\nyou can specify maximum of 10 message objects in the array;\nNote: for Perplexity models, messages must strictly alternate between user and AI roles (user → ai);\nexample:\n\"message_chain\": [{\"role\":\"user\",\"message\":\"Hello, what’s up?\"},{\"role\":\"ai\",\"message\":\"Hello! I’m doing well, thank you. How can I assist you today?\"}]",
+ "items": {
+ "anyOf": [
+ {
+ "properties": {
+ "message": {
+ "description": "message text",
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "role": {
+ "description": "role of the user from whom the message originates",
+ "type": [
+ "string",
+ "null"
+ ]
+ }
+ },
+ "type": "object"
+ }
+ ],
+ "type": [
+ "object",
+ "null"
+ ]
+ },
+ "type": [
+ "array",
+ "null"
+ ]
+ },
+ "model_name": {
+ "description": "<em>name of the AI model</em><br><strong>required field</strong><br><code>model_name</code >consists of the actual model name and version name;<br>if the basic model name is specified, its latest version will be set by default;<br>for example, if <code>gemini-1.5-pro</code> is specified, the <code>gemini-1.5-pro-002</code> will be set as <code>model_name</code> automatically;<br>you can receive the list of available LLM models by making a separate request to the <code>https://api.dataforseo.com/v3/ai_optimization/gemini/llm_responses/models</code>",
+ "type": "string"
+ },
+ "system_message": {
+ "description": "<em>instructions for the AI behavior</em><br>optional field<br>defines the AI's role, tone, or specific behavior <br>you can specify <strong>up to 500 characters</strong> in the <code>system_message</code> field",
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "tag": {
+ "description": "<em>user-defined task identifier</em><br>optional field<br><em>the character limit is 255</em><br>you can use this parameter to identify the task and match it with the result<br>you will find the specified <code>tag</code> value in the <code>data</code> object of the response",
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "temperature": {
+ "description": "<em>randomness of the AI response</em><br>optional field<br>higher values make output more diverse <br>lower values make output more focused<br>minimum value: <code>0</code><br>maximum value: <code>2</code><br>default value: <code>1.3</code>",
+ "type": [
+ "number",
+ "null"
+ ]
+ },
+ "top_p": {
+ "description": "<em>diversity of the AI response</em><br>optional field <br>controls diversity of the response by limiting token selection<br>minimum value: <code>0</code><br>maximum value: <code>1</code> <br>default value: <code>0.9</code>",
+ "type": [
+ "number",
+ "null"
+ ]
+ },
+ "use_reasoning": {
+ "description": "<em>enable reasoning for the AI model</em><br>optional field<br>when enabled, the model will perform reasoning before generating a response<br>refer to the <a href=\"https://docs.dataforseo.com/v3/ai_optimization/gemini/llm_responses/models/\" target=\"_blank\">Models endpoint</a> for a list of models that support <code>reasoning</code><br>default value: <code>false</code><br><strong>Note:</strong> if set to <code>true</code>, the minimum value for <code>max_output_tokens</code> is <code>1024</code><br><strong>Note #2:</strong> for Gemini Pro models, the <code>use_reasoning</code> will automatically be set to <code>true</code>",
+ "type": [
+ "boolean",
+ "null"
+ ]
+ },
+ "user_prompt": {
+ "description": "<em>prompt for the AI model</em><br><strong>required field</strong><br>the question or task you want to send to the AI model;<br>you can specify <strong>up to 500 characters</strong> in the <code>user_prompt</code> field",
+ "type": "string"
+ },
+ "web_search": {
+ "description": "<em>enable web search for current information</em><br>optional field<br>when enabled, the AI model can access and cite current web information;<br><strong>Note:</strong> refer to the <a href=\"https://docs.dataforseo.com/v3/ai_optimization/gemini/llm_responses/models/\">Models endpoint</a> for a list of models that support <code>web_search</code>; <br>default value: <code>false</code>;<br>The cost of the parameter can be calculated on the <a title=\"Gemini API Pricing\" href=\"https://ai.google.dev/gemini-api/docs/pricing\" target=\"_blank\" rel=\"noopener noreferrer\">Pricing</a> page",
+ "type": [
+ "boolean",
+ "null"
+ ]
+ }
+ },
+ "type": "object"
+ }
+]Input schema / properties / body / items / propertiesRemoved value: -{
- "max_output_tokens": {
- "description": "maximum number of tokens in the AI response optional field minimum value: 1 maximum value: 4096; default value: 2048; Note: if web_search is set to true or the reasoning model is specified in the request, the output token count may exceed the specified max_output_tokens limit Note #2: if use_reasoning is set to true, the minimum value for max_output_tokens is 1024",
- "type": "integer"
- },
- "message_chain": {
- "description": "conversation history optional field array of message objects representing previous conversation turns; each object must contain: role string with either user or ai role; message string with message content (max 500 characters); you can specify maximum of 10 message objects in the array; Note: for Perplexity models, messages must strictly alternate between user and AI roles (user → ai); example: \"message_chain\": [{\"role\":\"user\",\"message\":\"Hello, what’s up?\"},{\"role\":\"ai\",\"message\":\"Hello! I’m doing well, thank you. How can I assist you today?\"}]",
- "items": {
- "properties": {
- "message": {
- "description": "message text",
- "type": "string"
- },
- "role": {
- "description": "role of the user from whom the message originates",
- "enum": [
- "user",
- "ai"
- ],
- "type": "string"
- }
- },
- "required": [
- "role",
- "message"
- ],
- "type": "object"
- },
- "type": "array"
- },
- "model_name": {
- "description": "name of the AI model required field model_nameconsists of the actual model name and version name; if the basic model name is specified, its latest version will be set by default; for example, if gemini-1.5-pro is specified, the gemini-1.5-pro-002 will be set as model_name automatically; you can receive the list of available LLM models by making a separate request to the https://api.dataforseo.com/v3/ai_optimization/gemini/llm_responses/models",
- "type": "string"
- },
- "system_message": {
- "description": "instructions for the AI behavior optional field defines the AI's role, tone, or specific behavior you can specify up to 500 characters in the system_message field",
- "type": "string"
- },
- "tag": {
- "description": "user-defined task identifier optional field the character limit is 255 you can use this parameter to identify the task and match it with the result you will find the specified tag value in the data object of the response",
- "type": "string"
- },
- "temperature": {
- "description": "randomness of the AI response optional field higher values make output more diverse lower values make output more focused minimum value: 0 maximum value: 2 default value: 1.3",
- "type": "number"
- },
- "top_p": {
- "description": "diversity of the AI response optional field controls diversity of the response by limiting token selection minimum value: 0 maximum value: 1 default value: 0.9",
- "type": "number"
- },
- "use_reasoning": {
- "description": "enable reasoning for the AI model optional field when enabled, the model will perform reasoning before generating a response refer to the Models endpoint for a list of models that support reasoning default value: false Note: if set to true, the minimum value for max_output_tokens is 1024 Note #2: for Gemini Pro models, the use_reasoning will automatically be set to true",
- "type": "boolean"
- },
- "user_prompt": {
- "description": "prompt for the AI model required field the question or task you want to send to the AI model; you can specify up to 500 characters in the user_prompt field",
- "type": "string"
- },
- "web_search": {
- "description": "enable web search for current information optional field when enabled, the AI model can access and cite current web information; Note: refer to the Models endpoint for a list of models that support web_search; default value: false",
- "type": "boolean"
- }
-}Input schema / properties / body / items / requiredRemoved value: -[
- "user_prompt",
- "model_name"
-]Input schema / properties / body / items / typePrevious value: -"object"New value: +[
+ "object",
+ "null"
+]Input schema / requiredPrevious value: -[
- "body"
-]New value: +[]Output schema / x-fastmcp-wrap-resultAdded value: +trueInput schema / properties / body / exampleRemoved value: -[
- {
- "max_output_tokens": 200,
- "message_chain": [
- {
- "message": "Hello, what’s up?",
- "role": "user"
- },
- {
- "message": "Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?",
- "role": "ai"
- }
- ],
- "model_name": "gemini-2.5-flash",
- "system_message": "communicate as if we are in a business meeting",
- "temperature": 0.3,
- "top_p": 0.5,
- "user_prompt": "provide information on how relevant the amusement park business is in France now",
- "web_search": true
- }
-]Input schema / properties / body / items / anyOfRemoved value: -[
- {
- "example": [
- {
- "max_output_tokens": 200,
- "message_chain": [
- {
- "message": "Hello, what’s up?",
- "role": "user"
- },
- {
- "message": "Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?",
- "role": "ai"
- }
- ],
- "model_name": "gemini-2.5-flash",
- "system_message": "communicate as if we are in a business meeting",
- "temperature": 0.3,
- "top_p": 0.5,
- "user_prompt": "provide information on how relevant the amusement park business is in France now",
- "web_search": true
- }
- ],
- "properties": {
- "max_output_tokens": {
- "description": "<em>maximum number of tokens in the AI response</em><br>optional field<br>minimum value: <code>1</code><br>maximum value: <code>4096</code>;<br>default value: <code>2048</code>;<br><strong>Note:</strong> if <code>web_search</code> is set to <code>true</code> or the reasoning model is specified in the request, the output token count may exceed the specified <code>max_output_tokens</code> limit<br><strong>Note #2:</strong> if <code>use_reasoning</code> is set to <code>true</code>, the minimum value for <code>max_output_tokens</code> is <code>1024</code>",
- "type": [
- "integer",
- "null"
- ]
- },
- "message_chain": {
- "description": "conversation history\noptional field\narray of message objects representing previous conversation turns;\neach object must contain:\nrole string with either user or ai role;\nmessage string with message content (max 500 characters);\nyou can specify maximum of 10 message objects in the array;\nNote: for Perplexity models, messages must strictly alternate between user and AI roles (user → ai);\nexample:\n\"message_chain\": [{\"role\":\"user\",\"message\":\"Hello, what’s up?\"},{\"role\":\"ai\",\"message\":\"Hello! I’m doing well, thank you. How can I assist you today?\"}]",
- "items": {
- "anyOf": [
- {
- "properties": {
- "message": {
- "description": "message text",
- "type": [
- "string",
- "null"
- ]
- },
- "role": {
- "description": "role of the user from whom the message originates",
- "type": [
- "string",
- "null"
- ]
- }
- },
- "type": "object"
- }
- ],
- "type": [
- "object",
- "null"
- ]
- },
- "type": [
- "array",
- "null"
- ]
- },
- "model_name": {
- "description": "<em>name of the AI model</em><br><strong>required field</strong><br><code>model_name</code >consists of the actual model name and version name;<br>if the basic model name is specified, its latest version will be set by default;<br>for example, if <code>gemini-1.5-pro</code> is specified, the <code>gemini-1.5-pro-002</code> will be set as <code>model_name</code> automatically;<br>you can receive the list of available LLM models by making a separate request to the <code>https://api.dataforseo.com/v3/ai_optimization/gemini/llm_responses/models</code>",
- "type": "string"
- },
- "system_message": {
- "description": "<em>instructions for the AI behavior</em><br>optional field<br>defines the AI's role, tone, or specific behavior <br>you can specify <strong>up to 500 characters</strong> in the <code>system_message</code> field",
- "type": [
- "string",
- "null"
- ]
- },
- "tag": {
- "description": "<em>user-defined task identifier</em><br>optional field<br><em>the character limit is 255</em><br>you can use this parameter to identify the task and match it with the result<br>you will find the specified <code>tag</code> value in the <code>data</code> object of the response",
- "type": [
- "string",
- "null"
- ]
- },
- "temperature": {
- "description": "<em>randomness of the AI response</em><br>optional field<br>higher values make output more diverse <br>lower values make output more focused<br>minimum value: <code>0</code><br>maximum value: <code>2</code><br>default value: <code>1.3</code>",
- "type": [
- "number",
- "null"
- ]
- },
- "top_p": {
- "description": "<em>diversity of the AI response</em><br>optional field <br>controls diversity of the response by limiting token selection<br>minimum value: <code>0</code><br>maximum value: <code>1</code> <br>default value: <code>0.9</code>",
- "type": [
- "number",
- "null"
- ]
- },
- "use_reasoning": {
- "description": "<em>enable reasoning for the AI model</em><br>optional field<br>when enabled, the model will perform reasoning before generating a response<br>refer to the <a href=\"https://docs.dataforseo.com/v3/ai_optimization/gemini/llm_responses/models/\" target=\"_blank\">Models endpoint</a> for a list of models that support <code>reasoning</code><br>default value: <code>false</code><br><strong>Note:</strong> if set to <code>true</code>, the minimum value for <code>max_output_tokens</code> is <code>1024</code><br><strong>Note #2:</strong> for Gemini Pro models, the <code>use_reasoning</code> will automatically be set to <code>true</code>",
- "type": [
- "boolean",
- "null"
- ]
- },
- "user_prompt": {
- "description": "<em>prompt for the AI model</em><br><strong>required field</strong><br>the question or task you want to send to the AI model;<br>you can specify <strong>up to 500 characters</strong> in the <code>user_prompt</code> field",
- "type": "string"
- },
- "web_search": {
- "description": "<em>enable web search for current information</em><br>optional field<br>when enabled, the AI model can access and cite current web information;<br><strong>Note:</strong> refer to the <a href=\"https://docs.dataforseo.com/v3/ai_optimization/gemini/llm_responses/models/\">Models endpoint</a> for a list of models that support <code>web_search</code>; <br>default value: <code>false</code>;<br>The cost of the parameter can be calculated on the <a title=\"Gemini API Pricing\" href=\"https://ai.google.dev/gemini-api/docs/pricing\" target=\"_blank\" rel=\"noopener noreferrer\">Pricing</a> page",
- "type": [
- "boolean",
- "null"
- ]
- }
- },
- "type": "object"
- }
-]Input schema / properties / body / items / propertiesAdded value: +{
+ "max_output_tokens": {
+ "description": "maximum number of tokens in the AI response optional field minimum value: 1 maximum value: 4096; default value: 2048; Note: if web_search is set to true or the reasoning model is specified in the request, the output token count may exceed the specified max_output_tokens limit Note #2: if use_reasoning is set to true, the minimum value for max_output_tokens is 1024",
+ "type": "integer"
+ },
+ "message_chain": {
+ "description": "conversation history optional field array of message objects representing previous conversation turns; each object must contain: role string with either user or ai role; message string with message content (max 500 characters); you can specify maximum of 10 message objects in the array; Note: for Perplexity models, messages must strictly alternate between user and AI roles (user → ai); example: \"message_chain\": [{\"role\":\"user\",\"message\":\"Hello, what’s up?\"},{\"role\":\"ai\",\"message\":\"Hello! I’m doing well, thank you. How can I assist you today?\"}]",
+ "items": {
+ "properties": {
+ "message": {
+ "description": "message text",
+ "type": "string"
+ },
+ "role": {
+ "description": "role of the user from whom the message originates",
+ "enum": [
+ "user",
+ "ai"
+ ],
+ "type": "string"
+ }
+ },
+ "required": [
+ "role",
+ "message"
+ ],
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "model_name": {
+ "description": "name of the AI model required field model_nameconsists of the actual model name and version name; if the basic model name is specified, its latest version will be set by default; for example, if gemini-1.5-pro is specified, the gemini-1.5-pro-002 will be set as model_name automatically; you can receive the list of available LLM models by making a separate request to the https://api.dataforseo.com/v3/ai_optimization/gemini/llm_responses/models",
+ "type": "string"
+ },
+ "system_message": {
+ "description": "instructions for the AI behavior optional field defines the AI's role, tone, or specific behavior you can specify up to 500 characters in the system_message field",
+ "type": "string"
+ },
+ "tag": {
+ "description": "user-defined task identifier optional field the character limit is 255 you can use this parameter to identify the task and match it with the result you will find the specified tag value in the data object of the response",
+ "type": "string"
+ },
+ "temperature": {
+ "description": "randomness of the AI response optional field higher values make output more diverse lower values make output more focused minimum value: 0 maximum value: 2 default value: 1.3",
+ "type": "number"
+ },
+ "top_p": {
+ "description": "diversity of the AI response optional field controls diversity of the response by limiting token selection minimum value: 0 maximum value: 1 default value: 0.9",
+ "type": "number"
+ },
+ "use_reasoning": {
+ "description": "enable reasoning for the AI model optional field when enabled, the model will perform reasoning before generating a response refer to the Models endpoint for a list of models that support reasoning default value: false Note: if set to true, the minimum value for max_output_tokens is 1024 Note #2: for Gemini Pro models, the use_reasoning will automatically be set to true",
+ "type": "boolean"
+ },
+ "user_prompt": {
+ "description": "prompt for the AI model required field the question or task you want to send to the AI model; you can specify up to 500 characters in the user_prompt field",
+ "type": "string"
+ },
+ "web_search": {
+ "description": "enable web search for current information optional field when enabled, the AI model can access and cite current web information; Note: refer to the Models endpoint for a list of models that support web_search; default value: false",
+ "type": "boolean"
+ }
+}Input schema / properties / body / items / requiredAdded value: +[
+ "user_prompt",
+ "model_name"
+]Input schema / properties / body / items / typePrevious value: -[
- "object",
- "null"
-]New value: +"object"Input schema / requiredPrevious value: -[]New value: +[
+ "body"
+]Output schema / x-fastmcp-wrap-resultRemoved value: -trueInput schema / properties / body / exampleAdded value: +[
+ {
+ "max_output_tokens": 200,
+ "message_chain": [
+ {
+ "message": "Hello, what’s up?",
+ "role": "user"
+ },
+ {
+ "message": "Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?",
+ "role": "ai"
+ }
+ ],
+ "model_name": "gemini-2.5-flash",
+ "system_message": "communicate as if we are in a business meeting",
+ "temperature": 0.3,
+ "top_p": 0.5,
+ "user_prompt": "provide information on how relevant the amusement park business is in France now",
+ "web_search": true
+ }
+]Input schema / properties / body / items / anyOfAdded value: +[
+ {
+ "example": [
+ {
+ "max_output_tokens": 200,
+ "message_chain": [
+ {
+ "message": "Hello, what’s up?",
+ "role": "user"
+ },
+ {
+ "message": "Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?",
+ "role": "ai"
+ }
+ ],
+ "model_name": "gemini-2.5-flash",
+ "system_message": "communicate as if we are in a business meeting",
+ "temperature": 0.3,
+ "top_p": 0.5,
+ "user_prompt": "provide information on how relevant the amusement park business is in France now",
+ "web_search": true
+ }
+ ],
+ "properties": {
+ "max_output_tokens": {
+ "description": "<em>maximum number of tokens in the AI response</em><br>optional field<br>minimum value: <code>1</code><br>maximum value: <code>4096</code>;<br>default value: <code>2048</code>;<br><strong>Note:</strong> if <code>web_search</code> is set to <code>true</code> or the reasoning model is specified in the request, the output token count may exceed the specified <code>max_output_tokens</code> limit<br><strong>Note #2:</strong> if <code>use_reasoning</code> is set to <code>true</code>, the minimum value for <code>max_output_tokens</code> is <code>1024</code>",
+ "type": [
+ "integer",
+ "null"
+ ]
+ },
+ "message_chain": {
+ "description": "conversation history\noptional field\narray of message objects representing previous conversation turns;\neach object must contain:\nrole string with either user or ai role;\nmessage string with message content (max 500 characters);\nyou can specify maximum of 10 message objects in the array;\nNote: for Perplexity models, messages must strictly alternate between user and AI roles (user → ai);\nexample:\n\"message_chain\": [{\"role\":\"user\",\"message\":\"Hello, what’s up?\"},{\"role\":\"ai\",\"message\":\"Hello! I’m doing well, thank you. How can I assist you today?\"}]",
+ "items": {
+ "anyOf": [
+ {
+ "properties": {
+ "message": {
+ "description": "message text",
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "role": {
+ "description": "role of the user from whom the message originates",
+ "type": [
+ "string",
+ "null"
+ ]
+ }
+ },
+ "type": "object"
+ }
+ ],
+ "type": [
+ "object",
+ "null"
+ ]
+ },
+ "type": [
+ "array",
+ "null"
+ ]
+ },
+ "model_name": {
+ "description": "<em>name of the AI model</em><br><strong>required field</strong><br><code>model_name</code >consists of the actual model name and version name;<br>if the basic model name is specified, its latest version will be set by default;<br>for example, if <code>gemini-1.5-pro</code> is specified, the <code>gemini-1.5-pro-002</code> will be set as <code>model_name</code> automatically;<br>you can receive the list of available LLM models by making a separate request to the <code>https://api.dataforseo.com/v3/ai_optimization/gemini/llm_responses/models</code>",
+ "type": "string"
+ },
+ "system_message": {
+ "description": "<em>instructions for the AI behavior</em><br>optional field<br>defines the AI's role, tone, or specific behavior <br>you can specify <strong>up to 500 characters</strong> in the <code>system_message</code> field",
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "tag": {
+ "description": "<em>user-defined task identifier</em><br>optional field<br><em>the character limit is 255</em><br>you can use this parameter to identify the task and match it with the result<br>you will find the specified <code>tag</code> value in the <code>data</code> object of the response",
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "temperature": {
+ "description": "<em>randomness of the AI response</em><br>optional field<br>higher values make output more diverse <br>lower values make output more focused<br>minimum value: <code>0</code><br>maximum value: <code>2</code><br>default value: <code>1.3</code>",
+ "type": [
+ "number",
+ "null"
+ ]
+ },
+ "top_p": {
+ "description": "<em>diversity of the AI response</em><br>optional field <br>controls diversity of the response by limiting token selection<br>minimum value: <code>0</code><br>maximum value: <code>1</code> <br>default value: <code>0.9</code>",
+ "type": [
+ "number",
+ "null"
+ ]
+ },
+ "use_reasoning": {
+ "description": "<em>enable reasoning for the AI model</em><br>optional field<br>when enabled, the model will perform reasoning before generating a response<br>refer to the <a href=\"https://docs.dataforseo.com/v3/ai_optimization/gemini/llm_responses/models/\" target=\"_blank\">Models endpoint</a> for a list of models that support <code>reasoning</code><br>default value: <code>false</code><br><strong>Note:</strong> if set to <code>true</code>, the minimum value for <code>max_output_tokens</code> is <code>1024</code><br><strong>Note #2:</strong> for Gemini Pro models, the <code>use_reasoning</code> will automatically be set to <code>true</code>",
+ "type": [
+ "boolean",
+ "null"
+ ]
+ },
+ "user_prompt": {
+ "description": "<em>prompt for the AI model</em><br><strong>required field</strong><br>the question or task you want to send to the AI model;<br>you can specify <strong>up to 500 characters</strong> in the <code>user_prompt</code> field",
+ "type": "string"
+ },
+ "web_search": {
+ "description": "<em>enable web search for current information</em><br>optional field<br>when enabled, the AI model can access and cite current web information;<br><strong>Note:</strong> refer to the <a href=\"https://docs.dataforseo.com/v3/ai_optimization/gemini/llm_responses/models/\">Models endpoint</a> for a list of models that support <code>web_search</code>; <br>default value: <code>false</code>;<br>The cost of the parameter can be calculated on the <a title=\"Gemini API Pricing\" href=\"https://ai.google.dev/gemini-api/docs/pricing\" target=\"_blank\" rel=\"noopener noreferrer\">Pricing</a> page",
+ "type": [
+ "boolean",
+ "null"
+ ]
+ }
+ },
+ "type": "object"
+ }
+]Input schema / properties / body / items / propertiesRemoved value: -{
- "max_output_tokens": {
- "description": "maximum number of tokens in the AI response optional field minimum value: 1 maximum value: 4096; default value: 2048; Note: if web_search is set to true or the reasoning model is specified in the request, the output token count may exceed the specified max_output_tokens limit Note #2: if use_reasoning is set to true, the minimum value for max_output_tokens is 1024",
- "type": "integer"
- },
- "message_chain": {
- "description": "conversation history optional field array of message objects representing previous conversation turns; each object must contain: role string with either user or ai role; message string with message content (max 500 characters); you can specify maximum of 10 message objects in the array; Note: for Perplexity models, messages must strictly alternate between user and AI roles (user → ai); example: \"message_chain\": [{\"role\":\"user\",\"message\":\"Hello, what’s up?\"},{\"role\":\"ai\",\"message\":\"Hello! I’m doing well, thank you. How can I assist you today?\"}]",
- "items": {
- "properties": {
- "message": {
- "description": "message text",
- "type": "string"
- },
- "role": {
- "description": "role of the user from whom the message originates",
- "enum": [
- "user",
- "ai"
- ],
- "type": "string"
- }
- },
- "required": [
- "role",
- "message"
- ],
- "type": "object"
- },
- "type": "array"
- },
- "model_name": {
- "description": "name of the AI model required field model_nameconsists of the actual model name and version name; if the basic model name is specified, its latest version will be set by default; for example, if gemini-1.5-pro is specified, the gemini-1.5-pro-002 will be set as model_name automatically; you can receive the list of available LLM models by making a separate request to the https://api.dataforseo.com/v3/ai_optimization/gemini/llm_responses/models",
- "type": "string"
- },
- "system_message": {
- "description": "instructions for the AI behavior optional field defines the AI's role, tone, or specific behavior you can specify up to 500 characters in the system_message field",
- "type": "string"
- },
- "tag": {
- "description": "user-defined task identifier optional field the character limit is 255 you can use this parameter to identify the task and match it with the result you will find the specified tag value in the data object of the response",
- "type": "string"
- },
- "temperature": {
- "description": "randomness of the AI response optional field higher values make output more diverse lower values make output more focused minimum value: 0 maximum value: 2 default value: 1.3",
- "type": "number"
- },
- "top_p": {
- "description": "diversity of the AI response optional field controls diversity of the response by limiting token selection minimum value: 0 maximum value: 1 default value: 0.9",
- "type": "number"
- },
- "use_reasoning": {
- "description": "enable reasoning for the AI model optional field when enabled, the model will perform reasoning before generating a response refer to the Models endpoint for a list of models that support reasoning default value: false Note: if set to true, the minimum value for max_output_tokens is 1024 Note #2: for Gemini Pro models, the use_reasoning will automatically be set to true",
- "type": "boolean"
- },
- "user_prompt": {
- "description": "prompt for the AI model required field the question or task you want to send to the AI model; you can specify up to 500 characters in the user_prompt field",
- "type": "string"
- },
- "web_search": {
- "description": "enable web search for current information optional field when enabled, the AI model can access and cite current web information; Note: refer to the Models endpoint for a list of models that support web_search; default value: false",
- "type": "boolean"
- }
-}Input schema / properties / body / items / requiredRemoved value: -[
- "user_prompt",
- "model_name"
-]Input schema / properties / body / items / typePrevious value: -"object"New value: +[
+ "object",
+ "null"
+]Input schema / requiredPrevious value: -[
- "body"
-]New value: +[]Output schema / x-fastmcp-wrap-resultAdded value: +trueInput schema / properties / body / items / properties / web_search / descriptionPrevious value: -"enable web search for current information optional field when enabled, the AI model can access and cite current web information; Note: refer to the Models endpoint for a list of models that support web_search; default value: false; The cost of the parameter can be calculated on the Pricing page"New value: +"enable web search for current information optional field when enabled, the AI model can access and cite current web information; Note: refer to the Models endpoint for a list of models that support web_search; default value: false"Input schema / properties / body / items / properties / message_chain / descriptionPrevious value: -"conversation history optional field array of message objects representing previous conversation turns; each object must contain role and message parameters: role string with either user or ai role; message string with message content (max 500 characters); you can specify the maximum of 10 message objects in the array; example: \"message_chain\": [{\"role\":\"user\",\"message\":\"Hello, what’s up?\"},{\"role\":\"ai\",\"message\":\"Hello! I’m doing well, thank you. How can I assist you today?\"}]"New value: +"conversation history optional field array of message objects representing previous conversation turns; each object must contain: role string with either user or ai role; message string with message content (max 500 characters); you can specify maximum of 10 message objects in the array; Note: for Perplexity models, messages must strictly alternate between user and AI roles (user → ai); example: \"message_chain\": [{\"role\":\"user\",\"message\":\"Hello, what’s up?\"},{\"role\":\"ai\",\"message\":\"Hello! I’m doing well, thank you. How can I assist you today?\"}]"Input schema / properties / body / items / properties / message_chain / items / properties / message / descriptionAdded value: +"message text"Input schema / properties / body / items / properties / message_chain / items / properties / role / descriptionAdded value: +"role of the user from whom the message originates"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the safety profile (readOnlyHint=false, destructiveHint=true, openWorldHint=true), so the bar is lower, but the description adds almost nothing behavioral beyond a cost snippet. It does not reconcile the counterintuitive non-read-only/destructive labeling with the word 'retrieve' used in the description, nor mention auth, rate limits, or latency.
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?
Two short sentences plus a clearly delimited pricing block, with the core purpose front-loaded. Nothing is padded, though the 'based on the input parameters' clause is filler that adds no 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?
An output schema exists so return values need not be described, and the payload is documented in the nested schema, so the fundamentals are covered. However, for a billable, open-world LLM query tool the description omits the routing guidance and behavioral context an agent needs to call it correctly versus its model siblings.
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?
Top-level schema description coverage is 0% – the single 'body' parameter has no description – and the tool description provides no compensating explanation of the request payload shape. Though the nested schema is richly documented internally, the description itself contributes no parameter-level meaning, leaving the burden entirely on the schema.
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 names a specific verb ('retrieve structured responses') and resource ('Gemini AI model'), and the tool name itself separates it from the ChatGPT/Claude/Perplexity LLM siblings. It stops short of explicitly stating when this Gemini endpoint is preferred over those siblings, so it is clear but not differentiated in prose.
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?
There is no guidance on when to use this endpoint, no prerequisites, and no mention of the sibling LLM endpoints (chat_gpt, claude, perplexity) that an agent would need to disambiguate against. The only usage-adjacent content is a billing estimate, which is cost information rather than routing guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.