Connect Gemini to Claude, ChatGPT, Cursor, Claude Code, Codex, Gemini, GitHub Copilot and any other MCP client, for your whole team. Metorial adds security, governance, and tracing, and gives everyone one Magic MCP URL to connect.
Ask your agent in plain language. Each of these maps to a real tool on the server.
Use the generate embeddings tool in Gemini
Use the count tokens tool in Gemini
Use the list cached contents tool in Gemini
Use the generate text tool in Gemini
Use the delete file tool in Gemini
Use the delete cached content tool in Gemini
Supported Tools
generate_embeddings
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 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 Cached Contents
List all cached content entries. Returns cached content metadata including model association, creation time, and expiration.
generate_text
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 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 Cached Content
Delete a cached content entry. The cached content will no longer be available for use in generation requests.
update_cached_content
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 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
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 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 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
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 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 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 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.
get_video_operation
Get Video Operation
Get the current state of a Veo long-running operation. When generation succeeds, downloads each generated MP4 and returns its bytes only as Slate attachments.
generate_video
Generate Video
Start asynchronous text-to-video, image-to-video, or first/last-frame video generation with a Gemini Developer API Veo model. Returns a long-running operation name for get_video_operation.
Enable Gemini in Metorial. In your Metorial portal, enable the Gemini MCP server and sign in with the account that owns the data. Access stays governed by your team policies.
Add a custom connector. Open Customize, then Connectors. Select Add, then Custom, then Web.
Paste your Metorial MCP URL. Name it Metorial, paste your Magic MCP URL (<your-magic-mcp-url>) and continue.
Sign in. Select Add and sign in to load Gemini tools.
Enable Gemini in Metorial. In your Metorial portal, enable the Gemini MCP server and sign in with the account that owns the data. Access stays governed by your team policies.
Add a custom MCP server. On ChatGPT web, open Plugins, select +, then Add custom MCP server.
Paste your Metorial MCP URL. Name it Metorial, paste your Magic MCP URL (<your-magic-mcp-url>), choose OAuth and accept the risk notice.
Create and install the plugin. Select Create as a plugin, install it and sign in to load Gemini tools.
Enable Gemini in Metorial. In your Metorial portal, enable the Gemini MCP server and sign in with the account that owns the data. Access stays governed by your team policies.
Add Metorial to your MCP config. Use ~/.cursor/mcp.json for every project, or .cursor/mcp.json for one.
Sign in. Open Customize in the sidebar, find Metorial and sign in to load Gemini tools.
{
"mcpServers":{
"metorial":{
"url":"<your-magic-mcp-url>"
}
}
}
Enable Gemini in Metorial. In your Metorial portal, enable the Gemini MCP server and sign in with the account that owns the data. Access stays governed by your team policies.
Add the server over HTTP. Add --scope user to use it in every project.
Sign in. Run /mcp, select Metorial and sign in to load Gemini tools.
claude mcp add --transport http metorial <your-magic-mcp-url>
Enable Gemini in Metorial. In your Metorial portal, enable the Gemini MCP server and sign in with the account that owns the data. Access stays governed by your team policies.
Add the server and sign in. The Codex CLI, IDE extension and ChatGPT desktop app share this config.
Check the connection. Type /mcp in Codex to see Metorial and its Gemini tools.
codex mcp add metorial --url <your-magic-mcp-url>
codex mcp login metorial
Run Gemini through the Metorial gateway
One governed layer for every app your agents reach, not a separate connector per tool.
Give Gemini and every other app to your whole team through one MCP gateway, behind your SSO.
Scope which teams and agents can use Gemini tools with role-based access control, and trace every call.
Prefer to run it yourself? Metorial is open source and self-hostable.
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.
Frequently asked questions
Common questions about connecting Gemini to AI agents with Metorial.
How many tools does the Gemini MCP server have?
The Gemini MCP server exposes 17 tools, including Generate Embeddings, Count Tokens, List Cached Contents. Each one is governed and traced through Metorial.
Does the Gemini MCP server support triggers?
Gemini exposes tools your agents call on demand; it does not publish event triggers yet. Everything still runs through one governed MCP URL.
Which AI clients can use the Gemini MCP server?
Any MCP client, including VS Code, Windsurf, Zed, OpenCode and Grok. Each one reaches the Gemini MCP server through the same Metorial URL.
How do I give only some teams access to Gemini?
Use role-based access control to decide which teams, users, and agents can use Gemini and which of its tools they can call.
Can I self-host the Gemini MCP server?
Yes. Metorial is open source, so you can run the Gemini MCP server yourself or use the hosted gateway.
Connect Gemini to production AI agents
See how Metorial gives your team governed access to Gemini, with tracing and security controls built in.