# How to integrate Gemini MCP with Claude Code

```json
{
  "title": "How to integrate Gemini MCP with Claude Code",
  "toolkit": "Gemini",
  "toolkit_slug": "gemini",
  "framework": "Claude Code",
  "framework_slug": "claude-code",
  "url": "https://composio.dev/toolkits/gemini/framework/claude-code",
  "markdown_url": "https://composio.dev/toolkits/gemini/framework/claude-code.md",
  "updated_at": "2026-05-12T10:12:37.656Z"
}
```

## Introduction

Manage your Gemini directly from Claude Code with zero worries about OAuth hassles, API-breaking issues, or reliability and security concerns.
You can do this in two different ways:
- Via [Composio Connect](https://dashboard.composio.dev/login?utm_source=toolkits&utm_medium=framework_template&utm_campaign=claude-code&utm_content=composio_connect&next=%2F~%2Forg%2Fconnect%2Fclients%2Fclaude-code) - Direct and easiest approach
- Via [Composio SDK](https://docs.composio.dev/docs?utm_source=toolkits&utm_medium=framework_template&utm_campaign=claude-code&utm_content=composio_sdk) - Programmatic approach with more control

## Also integrate Gemini with

- [ChatGPT](https://composio.dev/toolkits/gemini/framework/chatgpt)
- [OpenAI Agents SDK](https://composio.dev/toolkits/gemini/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/gemini/framework/claude-agents-sdk)
- [Claude Cowork](https://composio.dev/toolkits/gemini/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/gemini/framework/codex)
- [Cursor](https://composio.dev/toolkits/gemini/framework/cursor)
- [VS Code](https://composio.dev/toolkits/gemini/framework/vscode)
- [OpenCode](https://composio.dev/toolkits/gemini/framework/opencode)
- [OpenClaw](https://composio.dev/toolkits/gemini/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/gemini/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/gemini/framework/cli)
- [Google ADK](https://composio.dev/toolkits/gemini/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/gemini/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/gemini/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/gemini/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/gemini/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/gemini/framework/crew-ai)

## TL;DR

- Only one MCP URL to connect multiple apps with Claude Code with zero auth hassles.
- Programmatic tool calling allows LLMs to write its code in a remote workbench to handle complex tool chaining. Reduces to-and-fro with LLMs for frequent tool calling.
- Handling Large tool responses out of LLM context to minimize context rot.
- Dynamic just-in-time access to 20,000 tools across 1000+ other Apps for cross-app workflows. It loads the tools you need, so LLMs aren't overwhelmed by tools you don't need.

## Connect Gemini to Claude Code

### Connecting Gemini to Claude Code using Composio
1. Add the Composio MCP to Claude

```bash
claude mcp add --scope user --transport http composio https://connect.composio.dev/mcp
```

## What is Claude Code?

Claude Code is Anthropic's command line developer tool that lets you use Claude directly inside your terminal. Instead of switching between your editor, browser, and chat, you can stay in your project folder and ask Claude to help you build, debug, refactor, and understand code right where you're working.
Key features include:
- Terminal-Native Experience: Work with Claude directly in your command line without switching contexts
- MCP Support: Built-in support for Model Context Protocol servers to extend Claude's capabilities
- Project Context: Claude understands your project structure and can read, write, and modify files
- Interactive Development: Ask questions, debug code, and get help in real-time while coding
- Multi-Platform: Works on macOS, Linux, WSL, and Windows

## What is the Gemini MCP server, and what's possible with it?

The Gemini MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Gemini account. It provides structured and secure access to Gemini's multimodal AI features, so your agent can generate text, images, and videos, analyze content, and manage model resources on your behalf.
- Text and content generation: Instruct your agent to create high-quality, customized text using Gemini's advanced generative models—great for brainstorming, drafting, or summarizing information.
- Creative image and video generation: Ask the agent to generate original images or high-quality videos from text prompts using Gemini 2.5 Flash and Veo models, with fine control over style and format.
- Embedding and semantic analysis: Let your agent transform any text into rich semantic embeddings for similarity search, clustering, or classification tasks.
- Model discovery and optimization: Have the agent list available Gemini and Veo models, check their capabilities, and select the best fit for your project or workflow.
- Efficient resource management: Enable the agent to track video generation operations, download final assets, and optimize prompt inputs by counting tokens—all without manual intervention.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `GEMINI_COUNT_TOKENS` | Count Tokens (Gemini) | Counts the number of tokens in text using Gemini tokenization. Useful for estimating costs, checking input limits, and optimizing prompts before making API calls. |
| `GEMINI_EMBED_CONTENT` | Embed Content (Gemini) | Generates text embeddings using Gemini embedding models. Converts text into numerical vectors for semantic search, similarity comparison, clustering, and classification tasks. |
| `GEMINI_GENERATE_CONTENT` | Generate Content (Gemini) | Generates text content or speech audio from prompts using Gemini models. Supports text generation models (Gemini Flash, Pro) and text-to-speech models with configurable parameters. Generated text is nested at results[i].response.data.text. Output may be wrapped in markdown fences (e.g., ```html...```) or preceded by explanatory prose; strip these before file writing or rendering. |
| `GEMINI_GENERATE_IMAGE` | Generate Image (Nano Banana) | Generates images from text prompts using Gemini models (Nano Banana). Supports models: 'gemini-2.5-flash-image' (GA stable, fast), 'gemini-3-pro-image-preview' (Nano Banana Pro - advanced with 4K resolution, thinking mode, up to 14 reference images), and 'gemini-2.0-flash-exp-image-generation' (2.0 Flash experimental). Returns one image per call; images are uploaded to S3. Parse response at data.image.s3url or the text-type entry in data.content — prefer the URL to avoid base64 blobs. Always validate s3url before treating call as successful; a 200 response may contain only text with no image. Store s3url immediately as URLs can expire. Output formats are raster only (JPG/PNG/WebP); request PNG for transparency. Concurrent usage may trigger HTTP 429/RESOURCE_EXHAUSTED — keep concurrency ≤3 and use exponential backoff (1s→2s→4s, ~5 retries). NOTE NEVER EVER TRUE SYNC_TO_WORKBENCH IN RUBE_MULTI_EXECUTE_TOOL |
| `GEMINI_GENERATE_VIDEOS` | Generate Videos (Veo) | Generates videos from text prompts using Google's Veo models. Returns an operation_name for tracking; pass it verbatim (no edits) to GEMINI_WAIT_FOR_VIDEO or GEMINI_GET_VIDEOS_OPERATION. Jobs take 30–180+ seconds; wait 10s before first poll, then poll every 10–30s (allow up to 12 min). Successful results include data.video_file.s3url — missing s3url means failure. If done=true but no video_file, check raiMediaFilteredReasons (safety block); revise prompt and regenerate. Text-only; cannot accept image inputs. Max ~3–5 concurrent jobs; 429 RESOURCE_EXHAUSTED requires exponential backoff. For retries, always start a fresh call — never reuse a failed operation_name. |
| `GEMINI_LIST_MODELS` | List Models (Gemini API) | Lists available Gemini and Veo models with their capabilities and limits. Useful for discovering supported models and their features before making generation requests. Before calling video generation tools, verify model availability here — preview Veo models (e.g., veo-3.0-generate-preview) may be unavailable or return missing video URIs; prefer stable models like veo-2.0-generate-001. |
| `GEMINI_WAIT_FOR_VIDEO` | Wait and Download Video (Veo) | Polls a Veo video generation operation until completion, then downloads and returns the video as a FileDownloadable. Generation takes 30–120+ seconds (up to ~10–12 min); long waits are normal, not failures. On completion, the URL is nested at data.video_file.s3url — validate it is non-empty before downstream use. A done=true response without a valid s3url indicates safety filter rejection (check raiMediaFilteredReasons) or quota exhaustion — adjust the prompt and regenerate. On timeout, use GEMINI_GET_VIDEOS_OPERATION with incremental backoff before starting a new job. Keep parallel jobs to 3–5 to avoid 429 RESOURCE_EXHAUSTED errors. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Gemini MCP server is an implementation of the Model Context Protocol that connects Claude Code (and other AI assistants like Claude and Cursor) directly to your Gemini account. It provides structured and secure access so Claude can perform Gemini operations on your behalf.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

Before starting, make sure you have:
- Claude Pro, Max, or API billing enabled Anthropic account
- Composio API Key
- A Gemini account
- Basic knowledge of Python or TypeScript

### 1. Install Claude Code

To install Claude Code, use one of the following methods based on your operating system:
```bash
# macOS, Linux, WSL
curl -fsSL https://claude.ai/install.sh | bash

# Windows PowerShell
irm https://claude.ai/install.ps1 | iex

# Windows CMD
curl -fsSL https://claude.ai/install.cmd -o install.cmd && install.cmd && del install.cmd
```

### 2. Set up Claude Code

Open a terminal, go to your project folder, and start Claude Code:
- Claude Code will open in your terminal
- Follow the prompts to sign in with your Anthropic account
- Complete the authentication flow
- Once authenticated, you can start using Claude Code
```bash
cd your-project-folder
claude
```

### 3. Set up environment variables

Create a .env file in your project root with the following variables:
- COMPOSIO_API_KEY authenticates with Composio (get it from [Composio dashboard](https://dashboard.composio.dev/login?utm_source=toolkits&utm_medium=framework_template&utm_campaign=claude-code&utm_content=api_key&next=%2F~%2Forg%2Fconnect%2Fclients%2Fclaude-code))
- USER_ID identifies the user for session management (use any unique identifier)
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
```

### 4. Install Composio library

No description provided.
```python
pip install composio-core python-dotenv
```

```typescript
npm install @composio/core dotenv
```

### 5. Generate Composio MCP URL

No description provided.
```python
import os
from composio import Composio
from dotenv import load_dotenv

load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
USER_ID = os.getenv("USER_ID")

composio_client = Composio(api_key=COMPOSIO_API_KEY)

composio_session = composio_client.create(
    user_id=USER_ID,
    toolkits=["gemini"],
)

COMPOSIO_MCP_URL = composio_session.mcp.url

print(f"MCP URL: {COMPOSIO_MCP_URL}")
print(f"\nUse this command to add to Claude Code:")
print(f'claude mcp add --transport http gemini-composio "{COMPOSIO_MCP_URL}" --headers "X-API-Key:{COMPOSIO_API_KEY}"')
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';

const { COMPOSIO_API_KEY, USER_ID } = process.env;

if (!COMPOSIO_API_KEY || !USER_ID) {
  throw new Error('COMPOSIO_API_KEY and USER_ID required in .env');
}

const composioClient = new Composio({ apiKey: COMPOSIO_API_KEY });

const composioSession = await composioClient.create(USER_ID, {
  toolkits: ['gemini'],
});

const composioMcpUrl = composioSession?.mcp.url;

console.log(`MCP URL: ${composioMcpUrl}`);
console.log(`\nUse this command to add to Claude Code:`);
console.log(`claude mcp add --transport http gemini-composio "${composioMcpUrl}" --headers "X-API-Key:${COMPOSIO_API_KEY}"`);
```

### 6. Run the script and copy the MCP URL

No description provided.
```python
python generate_mcp_url.py
```

```typescript
node --loader ts-node/esm generate_mcp_url.ts
# or if using tsx
tsx generate_mcp_url.ts
```

### 7. Add Gemini MCP to Claude Code

In your terminal, add the MCP server using the command from the previous step. The command format is:
- claude mcp add registers a new MCP server with Claude Code
- --transport http specifies that this is an HTTP-based MCP server
- The server name (gemini-composio) is how you'll reference it
- The URL points to your Composio Tool Router session
- --headers includes your Composio API key for authentication
After running the command, close the current Claude Code session and start a new one for the changes to take effect.
```bash
claude mcp add --transport http gemini-composio "YOUR_MCP_URL_HERE" --headers "X-API-Key:YOUR_COMPOSIO_API_KEY"

# Then restart Claude Code
exit
claude
```

### 8. Verify the installation

Check that your Gemini MCP server is properly configured.
- This command lists all MCP servers registered with Claude Code
- You should see your gemini-composio entry in the list
- This confirms that Claude Code can now access Gemini tools
If everything is wired up, you should see your gemini-composio entry listed:
```bash
claude mcp list
```

### 9. Authenticate Gemini

The first time you try to use Gemini tools, you'll be prompted to authenticate.
- Claude Code will detect that you need to authenticate with Gemini
- It will show you an authentication link
- Open the link in your browser (or copy/paste it)
- Complete the Gemini authorization flow
- Return to the terminal and start using Gemini through Claude Code
Once authenticated, you can ask Claude Code to perform Gemini operations in natural language. For example:
- "Summarize this research article in 100 words"
- "Generate a creative image of a futuristic city"
- "Create a 30-second video based on this script"

## Complete Code

```python
import os
from composio import Composio
from dotenv import load_dotenv

load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
USER_ID = os.getenv("USER_ID")

composio_client = Composio(api_key=COMPOSIO_API_KEY)

composio_session = composio_client.create(
    user_id=USER_ID,
    toolkits=["gemini"],
)

COMPOSIO_MCP_URL = composio_session.mcp.url

print(f"MCP URL: {COMPOSIO_MCP_URL}")
print(f"\nUse this command to add to Claude Code:")
print(f'claude mcp add --transport http gemini-composio "{COMPOSIO_MCP_URL}" --headers "X-API-Key:{COMPOSIO_API_KEY}"')
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';

const { COMPOSIO_API_KEY, USER_ID } = process.env;

if (!COMPOSIO_API_KEY || !USER_ID) {
  throw new Error('COMPOSIO_API_KEY and USER_ID required in .env');
}

const composioClient = new Composio({ apiKey: COMPOSIO_API_KEY });

const composioSession = await composioClient.create(USER_ID, {
  toolkits: ['gemini'],
});

const composioMcpUrl = composioSession?.mcp.url;

console.log(`MCP URL: ${composioMcpUrl}`);
console.log(`\nUse this command to add to Claude Code:`);
console.log(`claude mcp add --transport http gemini-composio "${composioMcpUrl}" --headers "X-API-Key:${COMPOSIO_API_KEY}"`);
```

## Conclusion

You've successfully integrated Gemini with Claude Code using Composio's MCP server. Now you can interact with Gemini directly from your terminal using natural language commands.
Key features of this setup:
- Terminal-native experience without switching contexts
- Natural language commands for Gemini operations
- Secure authentication through Composio's managed MCP
- Tool Router for dynamic tool discovery and execution
Next steps:
- Try asking Claude Code to perform various Gemini operations
- Add more toolkits to your Tool Router session for multi-app workflows
- Integrate this setup into your development workflow for increased productivity
You can extend this by adding more toolkits, implementing custom workflows, or building automation scripts that leverage Claude Code's capabilities.

## How to build Gemini MCP Agent with another framework

- [ChatGPT](https://composio.dev/toolkits/gemini/framework/chatgpt)
- [OpenAI Agents SDK](https://composio.dev/toolkits/gemini/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/gemini/framework/claude-agents-sdk)
- [Claude Cowork](https://composio.dev/toolkits/gemini/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/gemini/framework/codex)
- [Cursor](https://composio.dev/toolkits/gemini/framework/cursor)
- [VS Code](https://composio.dev/toolkits/gemini/framework/vscode)
- [OpenCode](https://composio.dev/toolkits/gemini/framework/opencode)
- [OpenClaw](https://composio.dev/toolkits/gemini/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/gemini/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/gemini/framework/cli)
- [Google ADK](https://composio.dev/toolkits/gemini/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/gemini/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/gemini/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/gemini/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/gemini/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/gemini/framework/crew-ai)

## Related Toolkits

- [Composio](https://composio.dev/toolkits/composio) - Composio is an integration platform that connects AI agents with hundreds of business tools. It streamlines authentication and lets you trigger actions across services—no custom code needed.
- [Composio search](https://composio.dev/toolkits/composio_search) - Composio search is a unified web search toolkit spanning travel, e-commerce, news, financial markets, images, and more. It lets you and your apps tap into up-to-date web data from a single, easy-to-integrate service.
- [Perplexityai](https://composio.dev/toolkits/perplexityai) - Perplexityai delivers natural, conversational AI models for generating human-like text. Instantly get context-aware, high-quality responses for chat, search, or complex workflows.
- [Browser tool](https://composio.dev/toolkits/browser_tool) - Browser tool is a virtual browser integration that lets AI agents interact with the web programmatically. It enables automated browsing, scraping, and action-taking from any AI workflow.
- [Ai ml api](https://composio.dev/toolkits/ai_ml_api) - Ai ml api is a suite of AI/ML models for natural language and image tasks. It provides fast, scalable access to advanced AI capabilities for your apps and workflows.
- [Aivoov](https://composio.dev/toolkits/aivoov) - Aivoov is an AI-powered text-to-speech platform offering 1,000+ voices in over 150 languages. Instantly turn written content into natural, human-like audio for any application.
- [All images ai](https://composio.dev/toolkits/all_images_ai) - All-Images.ai is an AI-powered image generation and management platform. It helps you create, search, and organize images effortlessly with advanced AI capabilities.
- [Anthropic administrator](https://composio.dev/toolkits/anthropic_administrator) - Anthropic administrator is an API for managing Anthropic organizational resources like members, workspaces, and API keys. It helps you automate admin tasks and streamline resource management across your Anthropic organization.
- [Api labz](https://composio.dev/toolkits/api_labz) - Api labz is a platform offering a suite of AI-driven APIs and workflow tools. It helps developers automate tasks and build smarter, more efficient applications.
- [Apipie ai](https://composio.dev/toolkits/apipie_ai) - Apipie ai is an AI model aggregator offering a single API for accessing top AI models from multiple providers. It helps developers build cost-efficient, latency-optimized AI solutions without juggling multiple integrations.
- [Astica ai](https://composio.dev/toolkits/astica_ai) - Astica ai provides APIs for computer vision, NLP, and voice synthesis. Integrate advanced AI features into your app with a single API key.
- [Bigml](https://composio.dev/toolkits/bigml) - BigML is a machine learning platform that lets you build, train, and deploy predictive models from your data. Its intuitive interface and robust API make machine learning accessible and efficient.
- [Botbaba](https://composio.dev/toolkits/botbaba) - Botbaba is a platform for building, managing, and deploying conversational AI chatbots across messaging channels. It streamlines chatbot automation, making it easier to integrate AI into customer interactions.
- [Botpress](https://composio.dev/toolkits/botpress) - Botpress is an open-source platform for building, deploying, and managing chatbots. It helps teams automate conversations and deliver rich, interactive messaging experiences.
- [Chatbotkit](https://composio.dev/toolkits/chatbotkit) - Chatbotkit is a platform for building and managing AI-powered chatbots using robust APIs and SDKs. It lets you easily add conversational AI to your apps for better user engagement.
- [Cody](https://composio.dev/toolkits/cody) - Cody is an AI assistant built for businesses, trained on your company's knowledge and data. It delivers instant answers and insights, tailored for your team.
- [Context7 MCP](https://composio.dev/toolkits/context7_mcp) - Context7 MCP delivers live, version-specific code docs and examples right from the source. It helps developers and AI agents instantly retrieve authoritative programming info—no more out-of-date docs.
- [Customgpt](https://composio.dev/toolkits/customgpt) - CustomGPT.ai lets you build and deploy chatbots tailored to your own data and business needs. Get precise and context-aware AI conversations without writing code.
- [Datarobot](https://composio.dev/toolkits/datarobot) - Datarobot is a machine learning platform that automates model development, deployment, and monitoring. It empowers organizations to quickly gain predictive insights from large datasets.
- [Deepgram](https://composio.dev/toolkits/deepgram) - Deepgram is an AI-powered speech recognition platform for accurate audio transcription and understanding. It enables fast, scalable speech-to-text with advanced audio intelligence features.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Gemini MCP?

With a standalone Gemini MCP server, the agents and LLMs can only access a fixed set of Gemini tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Gemini and many other apps based on the task at hand, all through a single MCP endpoint.

### Can I use Tool Router MCP with Claude Code?

Yes, you can. Claude Code fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Gemini tools.

### Can I manage the permissions and scopes for Gemini while using Tool Router?

Yes, absolutely. You can configure which Gemini scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

### How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Gemini data and credentials are handled as safely as possible.

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)