generate_embeddings
Generate vector embeddings for text content using Gemini embedding models. Supports single and batch embedding generation with configurable task type and dimensionality. Useful for semantic search, classification, and clustering.
count_tokens
Count the number of tokens in text content for a specific Gemini model. Useful for estimating costs and ensuring prompts fit within model token limits before sending generation requests.
list_cached_contents
List all cached content entries. Returns cached content metadata including model association, creation time, and expiration.
generate_text
Generate text using Gemini models with multimodal input support. Supports single-turn and multi-turn conversations with text, images, audio, video, and document inputs. Configure generation parameters, safety settings, system instructions, JSON output mode, and function calling.
delete_file
Delete a file previously uploaded to the Gemini File API. The file will no longer be available for use in generation requests.
delete_cached_content
Delete a cached content entry. The cached content will no longer be available for use in generation requests.
update_cached_content
Update the TTL or expiration time of existing cached content. Use this to extend or shorten the lifetime of a cache entry.
list_models
List available Gemini models and their capabilities. Returns model names, supported generation methods, token limits, and other metadata. Use this to discover which models are available and their specifications.
list_files
List files previously uploaded to the Gemini File API. Files are stored for 48 hours and can be referenced in generation requests by their URI.
get_file
Get metadata for a file previously uploaded to the Gemini File API. Returns file details including processing state, size, MIME type, and expiration time.
generate_image
Generate or edit images using Gemini's native image generation capabilities or Imagen models. Supports text-to-image generation and image editing with text prompts. Returns generated images as base64-encoded data.
create_cached_content
Create cached content to save and reuse precomputed input tokens. Caching is useful when repeatedly prompting with the same large context (e.g., a long document or system instructions). Cached content can be referenced in subsequent generation requests for cost and latency savings.
get_model
Get metadata for a specific Gemini model, including supported generation methods, token limits, version, and generation defaults. Use this before invoking a model-specific capability such as text generation, embeddings, or token counting.
get_cached_content
Get metadata for a cached content entry. The API returns cache metadata such as model, display name, token usage, and expiration, but not the original cached content body.
upload_file
Upload a text, image, audio, video, or document file to the Gemini File API for reuse in generation requests. Returns the file URI needed for fileData parts in Generate Text and cached content workflows.
Manage repositories, issues, and pull requests. Create and configure branches, star repositories, review code, and merge changes. Automate CI/CD workflows with GitHub Actions, manage workflow runs, secrets, and artifacts. Track issues with labels, milestones, and assignees. Search across code, repositories, issues, and users. Manage organizations, teams, and memberships. Create and manage projects, gists, packages, deployments, and environments. Access security alerts including code scanning, secret scanning, and Dependabot alerts. Read and write file contents in repositories. Manage webhooks, notifications, and codespaces.
Manage SharePoint sites, document libraries, lists, and files. Create, read, update, and delete lists and list items with custom columns. Upload, download, move, copy, and version files in document libraries. Search across sites, files, folders, lists, and list items using Microsoft Search. Manage permissions at site, list, and item levels with granular access control. Define and manage content types and site columns. Subscribe to webhooks for list and library change notifications. Retrieve site properties and search for sites across Microsoft 365.
Manage CRM data including Accounts, Contacts, Leads, Opportunities, Cases, and custom objects. Create, read, update, and delete records. Query data using SOQL and search across objects using SOSL. Perform bulk data operations for large-scale imports, exports, and migrations. Execute composite requests to batch multiple operations in a single API call. Access analytics, reports, and dashboards. Manage files and attachments associated with records. Interact with Chatter feeds, posts, and groups for social collaboration. Subscribe to real-time change events via Change Data Capture and Platform Events. Manage org metadata including custom objects, fields, layouts, and workflows. Query data using GraphQL for precise data retrieval across related objects.
Create, read, update, and delete records in Airtable bases and tables. Manage base schemas including creating tables and fields. Filter records using formulas, sort by fields, and scope queries to specific views. Upsert records to find, create, or update in a single call. Upload attachments to records, read and write record comments, list accessible bases, and receive real-time base change events through webhooks.
Create, read, update, and delete pages, blog posts, comments, and attachments in Confluence spaces. Manage spaces, permissions, labels, and content restrictions. Search content using Confluence Query Language (CQL). Upload and download file attachments with versioning. Manage users, groups, and group memberships. Create and manage whiteboards, databases, folders, and templates. View and update inline tasks. Access audit logs. Listen for webhooks on page, blog, comment, attachment, space, label, and user events.
Manage Git repositories, pull requests, and CI/CD pipelines on Bitbucket Cloud. Create, fork, and configure repositories within workspaces and projects. Create, review, approve, merge, and decline pull requests with inline code comments. Browse source code, list commits, and manage branches and tags. Track issues with the built-in issue tracker. Trigger, monitor, and manage Bitbucket Pipelines. List workspace members, configure repository default reviewers and branch restrictions, create and manage repository webhooks, and search code across repositories.
Generate text, chat responses, and structured outputs using Google's multimodal Gemini AI models. Process and understand mixed inputs including text, images, audio, video, and PDF documents. Generate images via Imagen and native models, generate videos via Veo, and create music with granular creative controls. Execute Python code within the model environment. Produce text, image, video, and audio embeddings for semantic search and classification. Upload and manage files for use in prompts. Fine-tune models with custom training data. Use built-in tools including Google Search grounding, URL context fetching, and computer use automation. Cache context for repeated use across requests. Count tokens before sending requests. Stream real-time voice and video interactions via the Live API over WebSockets. Call external functions and chain multiple tool invocations to fulfill complex requests.
Common questions about connecting Gemini to AI agents with Metorial.
