Integration

Google Gemini integration

Google's multimodal AI model API for text, image, audio, and code generation. Generate content with Gemini models, create embeddings for semantic search, stream responses in real-time, count tokens for cost estimation, cache context for efficiency, fine-tune models on custom data, and manage uploaded files. Supports advanced generation controls, safety settings, structured output, function calling, grounded answers, and batch processing. Perfect for building AI-powered applications, chatbots, content generation tools, semantic search systems, and agentic workflows.

Connect Google Gemini How integrations work

Ask it in chat

Say what should happen.
The workflow builds itself.

When this happens, do that in Google Gemini.Built from the 27 Google Gemini tools below, on the connection you add once.

Common Google Gemini use cases

Verify file upload status
Audit uploaded media files
Build semantic search engines
Monitor active cached content
Build fact-checked Q&A systems
Discover available tuned models
Remove sensitive cached content
Rename tuned models for clarity
Create domain-specific AI models
Remove deprecated model versions

What you can do with Google Gemini

Each of these is one operation on one endpoint, available both as a workflow step and as a tool an AI agent can call on its own. Nothing bundles several operations into one action, so what a run did stays readable afterwards.

Most endpoints run on the free plan. A few, mainly the ones that publish on your behalf, need a paid plan.

Tunedmodel, 6 operations

create_tuned_modelCreate tuned modelPOSTCreates a fine-tuned model from training examples using supervised tuning.
delete_tuned_modelDelete tuned modelDELETEPermanently deletes a fine-tuned model.
get_tuned_modelGet tuned modelGETRetrieves detailed information about a specific fine-tuned model.
list_tuned_modelsList tuned modelsGETRetrieves a paginated list of all fine-tuned models.
transfer_tuned_model_ownershipTransfer tuned model ownershipPOSTTransfers ownership of a tuned model to another user.
update_tuned_modelUpdate tuned modelPATCHUpdates properties of a fine-tuned model such as display name or description.

Cachedcontent, 5 operations

create_cached_contentCreate cached contentPOSTCreates cached content for efficient reuse across multiple generation requests.
delete_cached_contentDelete cached contentDELETEPermanently deletes a cached content entry before its automatic expiration.
get_cached_contentGet cached contentGETRetrieves detailed information about a specific cached content entry.
list_cached_contentsList cached contentsGETRetrieves a paginated list of all cached content entries.
update_cached_contentUpdate cached contentPATCHUpdates the TTL or expiration time of an existing cached content entry.

Generation, 5 operations

batch_generate_contentBatch generate contentPOSTProcesses multiple content generation requests in a single batch operation.
generate_contentGenerate contentPOSTGenerates AI-powered content using Google Gemini multimodal models with customizable parameters and safety settings.
generate_content_tunedGenerate content tunedPOSTGenerates content using a fine-tuned model with customized behavior.
stream_generate_contentStream generate contentPOSTStreams generated content in real-time as tokens are produced, enabling responsive user experiences.
stream_generate_content_tunedStream generate content tunedPOSTStreams generated content from a fine-tuned model in real-time as tokens are produced.

File, 4 operations

delete_fileDelete fileDELETEPermanently deletes an uploaded file before its automatic expiration.
get_fileGet fileGETRetrieves detailed metadata for a specific uploaded file.
list_filesList filesGETRetrieves a paginated list of all uploaded files with their metadata.
upload_fileUpload filePOSTUploads a media file for use with multimodal Gemini models and returns file metadata.

Embedding, 2 operations

batch_embed_contentsBatch embed contentsPOSTEfficiently generates vector embeddings for multiple text contents in a single API request.
embed_contentEmbed contentPOSTGenerates vector embeddings from text content for semantic search and similarity tasks.

Model, 2 operations

get_modelGet modelGETRetrieves detailed specifications and capabilities for a specific Gemini model.
list_modelsList modelsGETRetrieves a paginated list of all available Gemini models with their capabilities and specifications.

Answer, 1 operation

generate_answerGenerate answerPOSTGenerates factual answers with source attribution, ideal for grounded question-answering applications.

Prediction, 1 operation

predictPredictPOSTGenerates predictions using the specified model with configurable parameters.

Token, 1 operation

count_tokensCount tokensPOSTCalculates the number of tokens in provided content before making generation requests.

Use Google Gemini from Claude Code, Cursor or Codex

Connect Google Gemini in LiveContext, create an API key in Settings, then add the LiveContext MCP server to your client. Its Google Gemini operations become tools the client can call, next to every other integration you connected.

Claude Code

claude mcp add --transport http livecontext https://livecontext.ai/mcp --header "X-API-Key: YOUR_API_KEY"

Codex (~/.codex/config.toml)

[mcp_servers.livecontext]
url = "https://livecontext.ai/mcp"

[mcp_servers.livecontext.http_headers]
"X-API-Key" = "YOUR_API_KEY"

Cursor, Claude Desktop and other JSON configs

{
  "mcpServers": {
    "livecontext": {
      "type": "http",
      "url": "https://livecontext.ai/mcp",
      "headers": {
        "X-API-Key": "YOUR_API_KEY"
      }
    }
  }
}

Set up the MCP server step by step

How to connect Google Gemini

Create your workspace
Sign up free. Nothing to install.
Connect Google Gemini once
Add your Google Gemini connection in Settings. Every tool from this integration reuses it, and secrets are encrypted at rest and visible only to you.
Describe the job in chat
The workflow builds itself in front of you and picks the endpoints it needs. Drag the steps yourself on the canvas whenever you would rather be explicit.

Google Gemini integration FAQ

What can you do with the Google Gemini integration?

LiveContext exposes 27 operations on Google Gemini, covering tunedmodel, cachedcontent, generation and file. Common uses include Verify file upload status, Audit uploaded media files and Build semantic search engines.