# Convex

```json
{
  "name": "Convex",
  "slug": "convex",
  "url": "https://composio.dev/toolkits/convex",
  "markdown_url": "https://composio.dev/toolkits/convex.md",
  "logo_url": "https://logos.composio.dev/api/convex",
  "categories": [
    "developer tools & devops"
  ],
  "is_composio_managed": false,
  "updated_at": "2026-06-18T09:21:44.444Z"
}
```

![Convex logo](https://logos.composio.dev/api/convex)

## Description

Securely connect your AI agents and chatbots (Claude, ChatGPT, Cursor, etc) with Convex MCP or direct API to query database records, run serverless functions, inspect app data, and manage backend workflows through natural language.

## Summary

Convex is a Backend-as-a-Service platform with a real-time database, serverless functions, and built-in authentication.
Use it to build reactive apps faster without managing backend infrastructure.

## Categories

- developer tools & devops

## Toolkit Details

- Tools: 19

## Images

- Logo: https://logos.composio.dev/api/convex

## Authentication

- **Api Key**
  - Type: `api_key`
  - Description: Api Key authentication for Convex.
  - Setup:
    - Configure Api Key credentials for Convex.
    - Use the credentials when creating an auth config in Composio.
- **Bearer Token**
  - Type: `bearer_token`
  - Description: Bearer Token authentication for Convex.
  - Setup:
    - Configure Bearer Token credentials for Convex.
    - Use the credentials when creating an auth config in Composio.

## Suggested Prompts

- List records from Convex tasks table
- Run Convex query for active users
- Inspect Convex deployment function logs

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `CONVEX_CREATE_DEPLOY_KEY` | Create deploy key | Tool to create a deploy key for use with the Convex CLI. Use when you need to generate credentials for CLI-based development or deployment workflows. The generated key provides administrative access to the specified deployment. |
| `CONVEX_CREATE_DEPLOYMENT` | Create Deployment | Tool to create a new deployment for a Convex project. Use when you need to create a development, production, or custom deployment. Specify the deployment type and optional configuration like class, reference, and region. |
| `CONVEX_CREATE_PROJECT` | Create Project | Tool to create a new project on a Convex team, optionally provisioning a dev or prod deployment. Use when you need to initialize a new Convex project in a team. |
| `CONVEX_DELETE_CUSTOM_DOMAIN` | Delete Custom Domain | Tool to remove a custom domain from a Convex deployment. Use when you need to delete a previously configured custom domain. |
| `CONVEX_DELETE_DEPLOYMENT` | Delete Deployment | Tool to delete a Convex deployment. Use when you need to permanently remove a deployment and all its data. WARNING: This action will delete all data and files in the deployment and cannot be undone. |
| `CONVEX_DELETE_PROJECT` | Delete project | Deletes a Convex project and all its deployments permanently. Use when you need to permanently remove a project and all associated data. This operation cannot be undone. |
| `CONVEX_EXECUTE_QUERY_BATCH` | Execute Query Batch | Tool to execute multiple Convex query functions in a single batch request. Use when you need to fetch data from multiple queries efficiently in one API call. |
| `CONVEX_GET_DEPLOYMENT` | Get Deployment Details | Tool to retrieve details about a Convex cloud deployment. Use when you need to get information about a specific deployment including its configuration, region, creation time, and status. |
| `CONVEX_GET_PROJECT_BY_ID` | Get Project by ID | Tool to retrieve detailed information about a specific Convex project by its ID. Use when you need to fetch project metadata including name, slug, team association, and creation time. |
| `CONVEX_GET_PROJECT_BY_SLUG` | Get Project by Slug | Tool to retrieve a Convex project by its slug within a team. Use when you need to fetch project details using human-readable identifiers instead of numeric IDs. |
| `CONVEX_GET_QUERY_TIMESTAMP` | Get Query Timestamp | Tool to get the latest timestamp for queries from Convex deployment. Use when you need to retrieve the current query timestamp from the Convex API. |
| `CONVEX_GET_TOKEN_DETAILS` | Get token details | Tool to retrieve token details for the authenticated token. Returns the team ID for team tokens or project ID for project tokens. Especially useful after receiving a token from an OAuth flow to identify which team or project it belongs to. |
| `CONVEX_LIST_DEPLOY_KEYS` | List Deploy Keys | Tool to list all deploy keys for a specified Convex deployment. Use when you need to view all authentication tokens that can be used to deploy to this deployment. |
| `CONVEX_LIST_DEPLOYMENT_CLASSES` | List deployment classes | Tool to list available deployment classes for a Convex team. Use when you need to check which deployment classes are available for a specific team. |
| `CONVEX_LIST_DEPLOYMENT_REGIONS` | List deployment regions | Tool to list available deployment regions for a Convex team. Use when you need to check which regions are available for deploying a team's backend. |
| `CONVEX_LIST_DEPLOYMENTS` | List Deployments | Tool to list all deployments for a Convex project. Use when you need to see all deployments (production, preview, or local) for a specific project. |
| `CONVEX_LIST_LOG_STREAMS` | List Log Streams | Tool to list all existing log stream configurations in a deployment. Use when you need to view configured log streaming destinations like Datadog, Webhook, Axiom, or Sentry. |
| `CONVEX_LIST_PROJECTS` | List Projects | Tool to list all projects for a specific Convex team. Use when you need to retrieve all projects associated with a team by team ID. |
| `CONVEX_UPDATE_DEPLOYMENT` | Update Deployment | Tool to update properties of an existing Convex deployment. Use when you need to modify deployment settings such as dashboard edit confirmation or deployment reference. Only the fields provided in the request are modified. |

## Supported Triggers

None listed.

## Installation and MCP Setup

### Path 1: SDK Installation

#### Path 1, Step 1: Install Composio

Install the Composio SDK
```python
pip install composio_openai
```

```typescript
npm install @composio/openai
```

#### Path 1, Step 2: Initialize Composio and Create Tool Router Session

Import and initialize Composio client, then create a Tool Router session
```python
from openai import OpenAI
from composio import Composio
from composio_openai import OpenAIResponsesProvider

composio = Composio(provider=OpenAIResponsesProvider())
openai = OpenAI()
session = composio.create(user_id='your-user-id')
```

```typescript
import OpenAI from 'openai';
import { Composio } from '@composio/core';
import { OpenAIResponsesProvider } from '@composio/openai';

const composio = new Composio({
  provider: new OpenAIResponsesProvider(),
});
const openai = new OpenAI({});
const session = await composio.create('your-user-id');
```

#### Path 1, Step 3: Execute Convex Tools via Tool Router with Your Agent

Get tools from Tool Router session and execute Convex actions with your Agent
```python
from openai import OpenAI
from composio import Composio
from composio_openai import OpenAIResponsesProvider

composio = Composio(provider=OpenAIResponsesProvider())
openai = OpenAI()
session = composio.create(user_id='your-user-id')

tools = session.tools
response = openai.responses.create(
  model='gpt-4.1',
  tools=tools,
  input=[{
    'role': 'user',
    'content': 'List records from my Convex tasks table and summarize the open tasks'
  }]
)
result = composio.provider.handle_tool_calls(
  response=response,
  user_id='your-user-id'
)
print(result)
```

```typescript
import OpenAI from 'openai';
import { Composio } from '@composio/core';
import { OpenAIResponsesProvider } from '@composio/openai';

const composio = new Composio({
  provider: new OpenAIResponsesProvider(),
});
const openai = new OpenAI({});
const session = await composio.create('your-user-id');

const tools = session.tools;
const response = await openai.responses.create({
  model: 'gpt-4.1',
  tools: tools,
  input: [{
    role: 'user',
    content: 'List records from my Convex tasks table and summarize the open tasks'
  }],
});
const result = await composio.provider.handleToolCalls(
  'your-user-id',
  response.output
);
console.log(result);
```

### Path 2: MCP Server Setup

#### Path 2, Step 1: Install Composio

Install the Composio SDK for Python or TypeScript
```python
pip install composio claude-agent-sdk
```

```typescript
npm install @composio/core ai @ai-sdk/openai @ai-sdk/mcp
```

#### Path 2, Step 2: Initialize Client and Create Tool Router Session

Import and initialize the Composio client, then create a Tool Router session for Convex
```python
from composio import Composio
from claude_agent_sdk import ClaudeSDKClient, ClaudeAgentOptions

composio = Composio(api_key='your-composio-api-key')
session = composio.create(user_id='your-user-id')
url = session.mcp.url
```

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

const composio = new Composio({ apiKey: 'your-api-key' });
const session = await composio.create('your-user-id');
console.log(`Tool Router session created: ${session.mcp.url}`);
```

#### Path 2, Step 3: Connect to AI Agent

Use the MCP server with your AI agent (Anthropic Claude or Mastra)
```python
import asyncio

options = ClaudeAgentOptions(
    permission_mode='bypassPermissions',
    mcp_servers={
        'tool_router': {
            'type': 'http',
            'url': url,
            'headers': {
                'x-api-key': 'your-composio-api-key'
            }
        }
    },
    system_prompt='You are a helpful assistant with access to Convex tools.',
    max_turns=10
)

async def main():
    async with ClaudeSDKClient(options=options) as client:
        await client.query('List records from my Convex tasks table and summarize the open tasks')
        async for message in client.receive_response():
            if hasattr(message, 'content'):
                for block in message.content:
                    if hasattr(block, 'text'):
                        print(block.text)

asyncio.run(main())
```

```typescript
import { openai } from '@ai-sdk/openai';
import { experimental_createMCPClient as createMCPClient } from '@ai-sdk/mcp';
import { generateText } from 'ai';

const client = await createMCPClient({
  transport: {
    type: 'http',
    url: session.mcp.url,
    headers: {
      'x-api-key': 'your-composio-api-key',
    },
  },
});

const tools = await client.tools();
const { text } = await generateText({
  model: openai('gpt-4o'),
  tools,
  messages: [{
    role: 'user',
    content: 'List records from my Convex tasks table and summarize the open tasks'
  }],
  maxSteps: 5,
});

console.log(`Agent: ${text}`);
```

## Why Use Composio?

### 1. AI Native Convex Integration

- Supports both Convex MCP and direct API based integrations
- Structured, LLM-friendly schemas so agents can safely query Convex data and call functions
- Use mcp.create() when you want a dedicated Convex MCP server for tools like Claude, Cursor, or custom agents

### 2. Managed Auth

- Store Convex API keys and bearer tokens securely instead of hard-coding them in agent code
- Create Convex auth configs with auth_configs.create(), then connect users with connected_accounts.link()
- Manage per user and per environment Convex credentials from one place

### 3. Agent Optimized Design

- Tools are shaped for language models, so agents know when to read data, call a query, or run a mutation
- Comprehensive execution logs help you see what ran, when it ran, and which Convex account was used
- Less glue code. Less guesswork. Your agent gets clean tools it can actually use.

### 4. Enterprise Grade Security

- Fine-grained access controls help you decide which agents and users can reach Convex
- Scoped, least privilege access for Convex projects, deployments, and backend actions
- Full audit trails make it easier to review agent activity and meet compliance needs

## Use Convex with any AI Agent Framework

Choose a framework you want to connect Convex with:

- [OpenAI Agents SDK](https://composio.dev/toolkits/convex/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/convex/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/convex/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/convex/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/convex/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/convex/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/convex/framework/hermes-agent)
- [Google ADK](https://composio.dev/toolkits/convex/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/convex/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/convex/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/convex/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/convex/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/convex/framework/crew-ai)
- [Pydantic AI](https://composio.dev/toolkits/convex/framework/pydantic-ai)
- [AutoGen](https://composio.dev/toolkits/convex/framework/autogen)

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## Frequently Asked Questions

### Do I need my own developer credentials to use Convex with Composio?

Yes, Convex requires you to configure your own API key credentials. Once set up, Composio handles secure credential storage and API request handling for you.

### Can I use multiple toolkits together?

Yes! Composio's Tool Router enables agents to use multiple toolkits. [Learn more](https://docs.composio.dev/tool-router/overview).

### Is Composio secure?

Composio is SOC 2 and ISO 27001 compliant with all data encrypted in transit and at rest. [Learn more](https://trust.composio.dev).

### What if the API changes?

Composio maintains and updates all toolkit integrations automatically, so your agents always work with the latest API versions.

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