# Mapflow.ai

```json
{
  "name": "Mapflow.ai",
  "slug": "mapflow",
  "url": "https://composio.dev/toolkits/mapflow",
  "markdown_url": "https://composio.dev/toolkits/mapflow.md",
  "logo_url": "https://logos.composio.dev/api/mapflow",
  "categories": [
    "data & analytics"
  ],
  "is_composio_managed": false,
  "updated_at": "2026-08-21T05:28:30.383Z"
}
```

![Mapflow.ai logo](https://logos.composio.dev/api/mapflow)

## Description

Securely connect your AI agents and chatbots (Claude, ChatGPT, Cursor, etc) with Mapflow.ai MCP or direct API to list projects, check processing status, manage imagery workflows, and query geospatial analysis results through natural language.

## Summary

Mapflow.ai is an AI platform for analyzing satellite and aerial imagery and managing geospatial processing projects.
It helps teams extract map-ready insights from imagery faster, with custom workflows and catalog access.

## Categories

- data & analytics

## Toolkit Details

- Tools: 10

## Images

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

## Authentication

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

## Suggested Prompts

- List recent Mapflow.ai processing projects
- Analyze satellite imagery for building footprints
- Check status of geospatial extraction jobs

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `MAPFLOW_CREATE_PROCESSING` | Create Processing (Consumes Credits) | CREDIT-CONSUMING: create and immediately start an asynchronous v2 imagery-analysis processing. Estimate first, verify the account balance and limits, then poll MAPFLOW_GET_PROCESSING every 30-60 seconds. |
| `MAPFLOW_CREATE_PROJECT` | Create Project | Create a Mapflow project container for organizing imagery-analysis processings. This does not start processing or consume processing credits. |
| `MAPFLOW_DOWNLOAD_PROCESSING_RESULT` | Download Processing Result | Download a completed processing's vector result as a GeoJSON file, optionally restricted to one AOI. Call only after MAPFLOW_GET_PROCESSING reports status OK. |
| `MAPFLOW_ESTIMATE_PROCESSING_COST` | Estimate Processing Cost | Estimate the credit cost of a v2 processing without starting it or consuming credits. Provide a model workflow ID and at least one of geometry or area_sq_km. |
| `MAPFLOW_GET_ACCOUNT_CAPABILITIES` | Get Account Capabilities | Return the connected Mapflow account's credit balance, processing and storage limits, available AI models and optional blocks, and imagery providers. Use this before estimating or starting a processing. |
| `MAPFLOW_GET_PROCESSING` | Get Processing | Get detailed status, progress, cost, errors, source configuration, and result-layer metadata for one current v2 processing. Poll no more often than every 30-60 seconds while it is running. |
| `MAPFLOW_GET_STORAGE_OVERVIEW` | Get Storage Overview | Return custom-imagery storage limits and usage together with the account's mosaics, so an agent can select existing uploaded imagery without separate discovery calls. |
| `MAPFLOW_LIST_PROCESSINGS` | List Processings | List current v2 processings. Omit project_id for the connected account's personal list, or provide project_id to include processings in a specific visible personal, shared, or team project. |
| `MAPFLOW_LIST_PROJECTS` | List Projects | List projects visible to the connected account, including personal and shared or team projects and the IDs needed to scope processing operations. |
| `MAPFLOW_SEARCH_IMAGERY_CATALOG` | Search Imagery Catalog | Search external imagery providers linked to the connected account for scenes or mosaics intersecting a GeoJSON AOI. Available inventory depends on account and provider entitlements; route access does not imply commercial imagery access. |

## 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 Mapflow.ai Tools via Tool Router with Your Agent

Get tools from Tool Router session and execute Mapflow.ai actions with your Agent
```python
tools = session.tools
response = openai.responses.create(
  model='gpt-4.1',
  tools=tools,
  input=[{
    'role': 'user',
    'content': 'List my recent Mapflow.ai projects and summarize their processing status'
  }]
)
result = composio.provider.handle_tool_calls(
  response=response,
  user_id='your-user-id'
)
print(result)
```

```typescript
const tools = session.tools;
const response = await openai.responses.create({
  model: 'gpt-4.1',
  tools: tools,
  input: [{
    role: 'user',
    content: 'List my recent Mapflow.ai projects and summarize their processing status'
  }],
});
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 Mapflow.ai
```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 Mapflow.ai tools.',
    max_turns=10
)

async def main():
    async with ClaudeSDKClient(options=options) as client:
        await client.query('List my recent Mapflow.ai projects and summarize their processing status')
        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 my recent Mapflow.ai projects and summarize their processing status'
  }],
  maxSteps: 5,
});

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

## Why Use Composio?

### 1. AI Native Mapflow.ai Integration

- Supports both Mapflow.ai MCP and direct API based integrations
- Structured, LLM-friendly schemas for reliable geospatial tool execution
- Rich coverage for querying projects, imagery workflows, processing jobs, and analysis results

### 2. Managed Auth

- Secure API key handling without hard-coding Mapflow.ai credentials in your agent code
- Central place to manage, scope, and revoke Mapflow.ai access
- Per user and per environment credentials for safer geospatial automation

### 3. Agent Optimized Design

- Tools are designed so AI agents can understand Mapflow.ai actions clearly and call them reliably
- Comprehensive execution logs so you know which imagery jobs, project queries, and workflow actions ran

### 4. Enterprise Grade Security

- Fine-grained RBAC so you control which agents and users can access Mapflow.ai
- Scoped, least privilege access to Mapflow.ai projects and imagery workflows
- Full audit trail of agent actions to support review and compliance

## Use Mapflow.ai with any AI Agent Framework

Choose a framework you want to connect Mapflow.ai with:

None listed.

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## Frequently Asked Questions

### Do I need my own developer credentials to use Mapflow.ai with Composio?

Yes, Mapflow.ai requires you to configure your own API key. 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)
