gemini

Server path: /gemini | Type: Application | PCID required: Yes Google AI models

Tools

Tool	Description
`gemini_generate_content`	Generate content using Google Gemini models
`gemini_chat`	Have a conversation using Gemini models
`gemini_analyze_image`	Analyze an image using Gemini vision capabilities
`gemini_embed_content`	Create embeddings for text using Gemini models
`gemini_list_models`	List available Gemini models
`gemini_count_tokens`	Count tokens in text for Gemini models
`gemini_generate_code`	Generate code using Gemini models optimized for programming
`gemini_summarize_text`	Summarize long text using Gemini models

gemini_generate_content

Generate content using Google Gemini models Parameters:

Parameter	Type	Required	Default	Description
`model`	string	No	`"gemini-2.5-flash"`	Gemini model to use
`prompt`	string	Yes	—	Text prompt for content generation
`temperature`	number	No	—	Sampling temperature
`topP`	number	No	—	Nucleus sampling parameter
`topK`	number	No	—	Top-k sampling parameter
`maxOutputTokens`	number	No	—	Maximum tokens to generate
`stopSequences`	string[]	No	—	Stop sequences to end generation

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID"
    },
    "model": {
      "type": "string",
      "default": "gemini-2.5-flash",
      "description": "Gemini model to use"
    },
    "prompt": {
      "type": "string",
      "description": "Text prompt for content generation"
    },
    "temperature": {
      "type": "number",
      "description": "Sampling temperature"
    },
    "topP": {
      "type": "number",
      "description": "Nucleus sampling parameter"
    },
    "topK": {
      "type": "number",
      "description": "Top-k sampling parameter"
    },
    "maxOutputTokens": {
      "type": "number",
      "description": "Maximum tokens to generate"
    },
    "stopSequences": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Stop sequences to end generation"
    }
  },
  "required": [
    "PCID",
    "prompt"
  ]
}

gemini_chat

Have a conversation using Gemini models Parameters:

Parameter	Type	Required	Default	Description
`model`	string	No	`"gemini-2.5-flash"`	Gemini model to use
`messages`	object[]	Yes	—	Conversation history
`temperature`	number	No	—	Sampling temperature
`maxOutputTokens`	number	No	—	Maximum tokens to generate

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID"
    },
    "model": {
      "type": "string",
      "default": "gemini-2.5-flash",
      "description": "Gemini model to use"
    },
    "messages": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "role": {
            "type": "string",
            "enum": [
              "user",
              "model"
            ],
            "description": "Message role"
          },
          "parts": {
            "type": "array",
            "items": {
              "type": "object",
              "properties": {
                "text": {
                  "type": "string",
                  "description": "Message text content"
                }
              }
            },
            "description": "Message parts"
          }
        }
      },
      "description": "Conversation history"
    },
    "temperature": {
      "type": "number",
      "description": "Sampling temperature"
    },
    "maxOutputTokens": {
      "type": "number",
      "description": "Maximum tokens to generate"
    }
  },
  "required": [
    "PCID",
    "messages"
  ]
}

gemini_analyze_image

Analyze an image using Gemini vision capabilities Parameters:

Parameter	Type	Required	Default	Description
`model`	string	No	`"gemini-2.5-flash"`	Gemini model with vision capabilities
`imageUrl`	string	No	—	URL of image to analyze
`imageBase64`	string	No	—	Base64 encoded image data
`prompt`	string	Yes	—	Question or instruction about the image
`temperature`	number	No	—	Sampling temperature
`maxOutputTokens`	number	No	—	Maximum tokens to generate

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID"
    },
    "model": {
      "type": "string",
      "default": "gemini-2.5-flash",
      "description": "Gemini model with vision capabilities"
    },
    "imageUrl": {
      "type": "string",
      "description": "URL of image to analyze"
    },
    "imageBase64": {
      "type": "string",
      "description": "Base64 encoded image data"
    },
    "prompt": {
      "type": "string",
      "description": "Question or instruction about the image"
    },
    "temperature": {
      "type": "number",
      "description": "Sampling temperature"
    },
    "maxOutputTokens": {
      "type": "number",
      "description": "Maximum tokens to generate"
    }
  },
  "required": [
    "PCID",
    "prompt"
  ]
}

gemini_embed_content

Create embeddings for text using Gemini models Parameters:

Parameter	Type	Required	Default	Description
`model`	string	No	`"text-embedding-004"`	Gemini embedding model
`content`	string	Yes	—	Text content to embed
`taskType`	string	No	—	Task type for embedding optimization
`title`	string	No	—	Optional title for the content

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID"
    },
    "model": {
      "type": "string",
      "default": "text-embedding-004",
      "description": "Gemini embedding model"
    },
    "content": {
      "type": "string",
      "description": "Text content to embed"
    },
    "taskType": {
      "type": "string",
      "enum": [
        "RETRIEVAL_QUERY",
        "RETRIEVAL_DOCUMENT",
        "SEMANTIC_SIMILARITY",
        "CLASSIFICATION",
        "CLUSTERING"
      ],
      "description": "Task type for embedding optimization"
    },
    "title": {
      "type": "string",
      "description": "Optional title for the content"
    }
  },
  "required": [
    "PCID",
    "content"
  ]
}

gemini_list_models

List available Gemini models

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID"
    }
  },
  "required": [
    "PCID"
  ]
}

gemini_count_tokens

Count tokens in text for Gemini models Parameters:

Parameter	Type	Required	Default	Description
`model`	string	No	`"gemini-2.5-flash"`	Gemini model for token counting
`text`	string	Yes	—	Text to count tokens for

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID"
    },
    "model": {
      "type": "string",
      "default": "gemini-2.5-flash",
      "description": "Gemini model for token counting"
    },
    "text": {
      "type": "string",
      "description": "Text to count tokens for"
    }
  },
  "required": [
    "PCID",
    "text"
  ]
}

gemini_generate_code

Generate code using Gemini models optimized for programming Parameters:

Parameter	Type	Required	Default	Description
`model`	string	No	`"gemini-2.5-flash"`	Gemini model to use
`prompt`	string	Yes	—	Code generation prompt
`language`	string	No	—	Programming language (e.g., “python”, “javascript”)
`temperature`	number	No	—	Low temperature for more deterministic code
`maxOutputTokens`	number	No	—	Maximum tokens to generate

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID"
    },
    "model": {
      "type": "string",
      "default": "gemini-2.5-flash",
      "description": "Gemini model to use"
    },
    "prompt": {
      "type": "string",
      "description": "Code generation prompt"
    },
    "language": {
      "type": "string",
      "description": "Programming language (e.g., \"python\", \"javascript\")"
    },
    "temperature": {
      "type": "number",
      "default": 0.1,
      "description": "Low temperature for more deterministic code"
    },
    "maxOutputTokens": {
      "type": "number",
      "description": "Maximum tokens to generate"
    }
  },
  "required": [
    "PCID",
    "prompt"
  ]
}

gemini_summarize_text

Summarize long text using Gemini models Parameters:

Parameter	Type	Required	Default	Description
`model`	string	No	`"gemini-2.5-flash"`	Gemini model to use
`text`	string	Yes	—	Text to summarize
`summaryLength`	string	No	`"medium"`	Desired summary length
`focusAreas`	string[]	No	—	Specific areas to focus on in summary

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID"
    },
    "model": {
      "type": "string",
      "default": "gemini-2.5-flash",
      "description": "Gemini model to use"
    },
    "text": {
      "type": "string",
      "description": "Text to summarize"
    },
    "summaryLength": {
      "type": "string",
      "enum": [
        "short",
        "medium",
        "long"
      ],
      "default": "medium",
      "description": "Desired summary length"
    },
    "focusAreas": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Specific areas to focus on in summary"
    }
  },
  "required": [
    "PCID",
    "text"
  ]
}

Triggers API

Platform API

Embedded MCP Servers

Application MCP Servers

Tools

gemini_generate_content

gemini_chat

gemini_analyze_image

gemini_embed_content

gemini_list_models

gemini_count_tokens

gemini_generate_code

gemini_summarize_text

Triggers API

Platform API

Embedded MCP Servers

Application MCP Servers

​Tools

​gemini_generate_content

​gemini_chat

​gemini_analyze_image

​gemini_embed_content

​gemini_list_models

​gemini_count_tokens

​gemini_generate_code

​gemini_summarize_text

Tools

gemini_generate_content

gemini_chat

gemini_analyze_image

gemini_embed_content

gemini_list_models

gemini_count_tokens

gemini_generate_code

gemini_summarize_text