# How to integrate Softr MCP with Vercel AI SDK v6

```json
{
  "title": "How to integrate Softr MCP with Vercel AI SDK v6",
  "toolkit": "Softr",
  "toolkit_slug": "softr",
  "framework": "Vercel AI SDK",
  "framework_slug": "ai-sdk",
  "url": "https://composio.dev/toolkits/softr/framework/ai-sdk",
  "markdown_url": "https://composio.dev/toolkits/softr/framework/ai-sdk.md",
  "updated_at": "2026-03-29T06:51:11.068Z"
}
```

## Introduction

This guide walks you through connecting Softr to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Softr agent that can list all users in your softr app, add a new record to products table, update user status to 'active' in softr through natural language commands.
This guide will help you understand how to give your Vercel AI SDK agent real control over a Softr account through Composio's Softr MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Softr with

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

## TL;DR

Here's what you'll learn:
- How to set up and configure a Vercel AI SDK agent with Softr integration
- Using Composio's Tool Router to dynamically load and access Softr tools
- Creating an MCP client connection using HTTP transport
- Building an interactive CLI chat interface with conversation history management
- Handling tool calls and results within the Vercel AI SDK framework

## What is Vercel AI SDK?

The Vercel AI SDK is a TypeScript library for building AI-powered applications. It provides tools for creating agents that can use external services and maintain conversation state.
Key features include:
- streamText: Core function for streaming responses with real-time tool support
- MCP Client: Built-in support for Model Context Protocol via @ai-sdk/mcp
- Step Counting: Control multi-step tool execution with stopWhen: stepCountIs()
- OpenAI Provider: Native integration with OpenAI models

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

The Softr MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Softr account. It provides structured and secure access so your agent can perform Softr operations on your behalf.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `SOFTR_CREATE_DATABASE` | Create Database | Tool to create a new database in a Softr workspace. Use when you need to set up a new database for storing data within a specific Softr workspace. |
| `SOFTR_CREATE_RECORD` | Create Record | Creates a new record in a Softr database table. Use when you need to add new data to a specific table in your Softr database. |
| `SOFTR_CREATE_TABLE` | Create Table | Tool to create a new table within a specified Softr database. Use when you need to add a new data structure with custom fields to organize information. |
| `SOFTR_CREATE_TABLE_FIELD` | Create Table Field | Tool to add a new field to a Softr table. Use when you need to add a new column to an existing table, such as adding an email field, a text field, or any other field type to store additional data. |
| `SOFTR_DELETE_DATABASE` | Delete database | Tool to delete a specific database by its ID from Softr. Use when you need to remove a database. The database must be empty unless the 'force' parameter is set to true. This operation is irreversible. |
| `SOFTR_DELETE_RECORD` | Delete Record | Tool to delete a record from a Softr database table. Use when you need to permanently remove a specific record. |
| `SOFTR_DELETE_TABLE` | Delete Table | Tool to delete a specific table by its ID from a database. Use when you need to remove a table. The table must be empty unless the force parameter is set to true. |
| `SOFTR_DELETE_TABLE_FIELD` | Delete Table Field | Tool to delete a field from a Softr database table. Use when you need to remove a field from a table. Returns success confirmation upon completion. |
| `SOFTR_GET_DATABASE` | Get Database | Tool to retrieve details for a specific database by ID. Use when you need to fetch information about a particular database in Softr. |
| `SOFTR_GET_DATABASES` | Get Databases | Tool to retrieve all databases available in the workspace. Use when you need to list or discover available databases for further operations. |
| `SOFTR_GET_RECORD` | Get Record | Tool to retrieve a single record by its ID from a Softr database table. Use when you need to fetch detailed information about a specific record. |
| `SOFTR_GET_RECORDS_FROM_TABLE` | Get records from table | Tool to retrieve a paginated list of records from a Softr table. Use when you need to fetch records from a specific table with optional pagination parameters. |
| `SOFTR_GET_TABLE` | Get Table | Tool to retrieve details for a specific table by ID. Use when you need to inspect table structure, fields, or metadata. |
| `SOFTR_GET_TABLE_FIELD` | Get Table Field | Tool to retrieve a specific field from a Softr table by field ID. Use when you need detailed configuration information about a table field, including its type, options, and metadata. |
| `SOFTR_GET_TABLE_FIELDS` | Get Table Fields | Tool to retrieve all fields for a specific table in a Softr database. Returns comprehensive field information including id, name, type, options, and metadata. Use when you need to inspect or work with table structure. |
| `SOFTR_GET_TABLES` | Get Tables | Retrieves all tables within a specified Softr database. Use when you need to list or explore the tables available in a database. |
| `SOFTR_GET_TABLE_VIEWS` | Get Table Views | Tool to retrieve all views for a specified table in a Softr database. Use when you need to list or inspect available views for a table. |
| `SOFTR_SEARCH_RECORDS` | Search Records | Tool to search records in a Softr database table with filtering and pagination. Use when you need to retrieve records from a specific table, optionally filtered by field values and paginated for large result sets. |
| `SOFTR_UPDATE_DATABASE` | Update Database | Tool to update an existing database's name and/or description. Use when you need to modify database metadata after creation. |
| `SOFTR_UPDATE_A_RECORD` | Update a record | Tool to update an existing record's field values in a Softr table. Use when you need to modify specific fields of a record by providing the database ID, table ID, record ID, and the new field values. |
| `SOFTR_UPDATE_TABLE` | Update Table | Tool to update a table's name and/or description in Softr Database. Use when you need to modify table metadata. To modify fields, use the field-specific endpoints instead. |
| `SOFTR_UPDATE_TABLE_FIELD` | Update table field | Updates an existing field in a Softr table. Use when you need to modify a field's name, type, or configuration options. Note: The API requires both 'type' and 'options' fields even if only updating the name. |

## Supported Triggers

None listed.

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

The Softr MCP server is an implementation of the Model Context Protocol that connects your AI agent to Softr. It provides structured and secure access so your agent can perform Softr operations on your behalf through a secure, permission-based interface.
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 you begin, make sure you have:
- Node.js and npm installed
- A Composio account with API key
- An OpenAI API key

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) and create an API key. You'll need credits to use the models, or you can connect to another model provider.
- Keep the API key safe.
Composio API Key
- Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install required dependencies

First, install the necessary packages for your project.
What you're installing:
- @ai-sdk/openai: Vercel AI SDK's OpenAI provider
- @ai-sdk/mcp: MCP client for Vercel AI SDK
- @composio/core: Composio SDK for tool integration
- ai: Core Vercel AI SDK
- dotenv: Environment variable management
```bash
npm install @ai-sdk/openai @ai-sdk/mcp @composio/core ai dotenv
```

### 3. Set up environment variables

Create a .env file in your project root.
What's needed:
- OPENAI_API_KEY: Your OpenAI API key for GPT model access
- COMPOSIO_API_KEY: Your Composio API key for tool access
- COMPOSIO_USER_ID: A unique identifier for the user session
```bash
OPENAI_API_KEY=your_openai_api_key_here
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here
```

### 4. Import required modules and validate environment

What's happening:
- We're importing all necessary libraries including Vercel AI SDK's OpenAI provider and Composio
- The dotenv/config import automatically loads environment variables
- The MCP client import enables connection to Composio's tool server
```typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Composio } from "@composio/core";
import * as readline from "readline";
import { streamText, type ModelMessage, stepCountIs } from "ai";
import { createMCPClient } from "@ai-sdk/mcp";

const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey,
});
```

### 5. Create Tool Router session and initialize MCP client

What's happening:
- We're creating a Tool Router session that gives your agent access to Softr tools
- The create method takes the user ID and specifies which toolkits should be available
- The returned mcp object contains the URL and authentication headers needed to connect to the MCP server
- This session provides access to all Softr-related tools through the MCP protocol
```typescript
async function main() {
  // Create a tool router session for the user
  const session = await composio.create(composioUserID!, {
    toolkits: ["softr"],
  });

  const mcpUrl = session.mcp.url;
```

### 6. Connect to MCP server and retrieve tools

What's happening:
- We're creating an MCP client that connects to our Composio Tool Router session via HTTP
- The mcp.url provides the endpoint, and mcp.headers contains authentication credentials
- The type: "http" is important - Composio requires HTTP transport
- tools() retrieves all available Softr tools that the agent can use
```typescript
const mcpClient = await createMCPClient({
  transport: {
    type: "http",
    url: mcpUrl,
    headers: session.mcp.headers, // Authentication headers for the Composio MCP server
  },
});

const tools = await mcpClient.tools();
```

### 7. Initialize conversation and CLI interface

What's happening:
- We initialize an empty messages array to maintain conversation history
- A readline interface is created to accept user input from the command line
- Instructions are displayed to guide the user on how to interact with the agent
```typescript
let messages: ModelMessage[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log(
  "Ask any questions related to softr, like summarize my last 5 emails, send an email, etc... :)))\n",
);

const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: "> ",
});

rl.prompt();
```

### 8. Handle user input and stream responses with real-time tool feedback

What's happening:
- We use streamText instead of generateText to stream responses in real-time
- toolChoice: "auto" allows the model to decide when to use Softr tools
- stopWhen: stepCountIs(10) allows up to 10 steps for complex multi-tool operations
- onStepFinish callback displays which tools are being used in real-time
- We iterate through the text stream to create a typewriter effect as the agent responds
- The complete response is added to conversation history to maintain context
- Errors are caught and displayed with helpful retry suggestions
```typescript
rl.on("line", async (userInput: string) => {
  const trimmedInput = userInput.trim();

  if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
    console.log("\nGoodbye!");
    rl.close();
    process.exit(0);
  }

  if (!trimmedInput) {
    rl.prompt();
    return;
  }

  messages.push({ role: "user", content: trimmedInput });
  console.log("\nAgent is thinking...\n");

  try {
    const stream = streamText({
      model: openai("gpt-5"),
      messages,
      tools,
      toolChoice: "auto",
      stopWhen: stepCountIs(10),
      onStepFinish: (step) => {
        for (const toolCall of step.toolCalls) {
          console.log(`[Using tool: ${toolCall.toolName}]`);
          }
          if (step.toolCalls.length > 0) {
            console.log(""); // Add space after tool calls
          }
        },
      });

      for await (const chunk of stream.textStream) {
        process.stdout.write(chunk);
      }

      console.log("\n\n---\n");

      // Get final result for message history
      const response = await stream.response;
      if (response?.messages?.length) {
        messages.push(...response.messages);
      }
    } catch (error) {
      console.error("\nAn error occurred while talking to the agent:");
      console.error(error);
      console.log(
        "\nYou can try again or restart the app if it keeps happening.\n",
      );
    } finally {
      rl.prompt();
    }
  });

  rl.on("close", async () => {
    await mcpClient.close();
    console.log("\n👋 Session ended.");
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});
```

## Complete Code

```typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Composio } from "@composio/core";
import * as readline from "readline";
import { streamText, type ModelMessage, stepCountIs } from "ai";
import { createMCPClient } from "@ai-sdk/mcp";

const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey,
});

async function main() {
  // Create a tool router session for the user
  const session = await composio.create(composioUserID!, {
    toolkits: ["softr"],
  });

  const mcpUrl = session.mcp.url;

  const mcpClient = await createMCPClient({
    transport: {
      type: "http",
      url: mcpUrl,
      headers: session.mcp.headers, // Authentication headers for the Composio MCP server
    },
  });

  const tools = await mcpClient.tools();

  let messages: ModelMessage[] = [];

  console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
  console.log(
    "Ask any questions related to softr, like summarize my last 5 emails, send an email, etc... :)))\n",
  );

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: "> ",
  });

  rl.prompt();

  rl.on("line", async (userInput: string) => {
    const trimmedInput = userInput.trim();

    if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
      console.log("\nGoodbye!");
      rl.close();
      process.exit(0);
    }

    if (!trimmedInput) {
      rl.prompt();
      return;
    }

    messages.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    try {
      const stream = streamText({
        model: openai("gpt-5"),
        messages,
        tools,
        toolChoice: "auto",
        stopWhen: stepCountIs(10),
        onStepFinish: (step) => {
          for (const toolCall of step.toolCalls) {
            console.log(`[Using tool: ${toolCall.toolName}]`);
          }
          if (step.toolCalls.length > 0) {
            console.log(""); // Add space after tool calls
          }
        },
      });

      for await (const chunk of stream.textStream) {
        process.stdout.write(chunk);
      }

      console.log("\n\n---\n");

      // Get final result for message history
      const response = await stream.response;
      if (response?.messages?.length) {
        messages.push(...response.messages);
      }
    } catch (error) {
      console.error("\nAn error occurred while talking to the agent:");
      console.error(error);
      console.log(
        "\nYou can try again or restart the app if it keeps happening.\n",
      );
    } finally {
      rl.prompt();
    }
  });

  rl.on("close", async () => {
    await mcpClient.close();
    console.log("\n👋 Session ended.");
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});
```

## Conclusion

You've successfully built a Softr agent using the Vercel AI SDK with streaming capabilities! This implementation provides a powerful foundation for building AI applications with natural language interfaces and real-time feedback.
Key features of this implementation:
- Real-time streaming responses for a better user experience with typewriter effect
- Live tool execution feedback showing which tools are being used as the agent works
- Dynamic tool loading through Composio's Tool Router with secure authentication
- Multi-step tool execution with configurable step limits (up to 10 steps)
- Comprehensive error handling for robust agent execution
- Conversation history maintenance for context-aware responses
You can extend this further by adding custom error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

## How to build Softr MCP Agent with another framework

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

## Related Toolkits

- [Google Sheets](https://composio.dev/toolkits/googlesheets) - Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly.
- [Notion](https://composio.dev/toolkits/notion) - Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place.
- [Airtable](https://composio.dev/toolkits/airtable) - Airtable combines the flexibility of spreadsheets with the power of a database for easy project and data management. Teams use Airtable to organize, track, and collaborate with custom views and automations.
- [Asana](https://composio.dev/toolkits/asana) - Asana is a collaborative work management platform for teams to organize and track projects. It streamlines teamwork, boosts productivity, and keeps everyone aligned on goals.
- [Google Tasks](https://composio.dev/toolkits/googletasks) - Google Tasks is a to-do list and task management tool integrated into Gmail and Google Calendar. It helps you organize, track, and complete tasks across your Google ecosystem.
- [Linear](https://composio.dev/toolkits/linear) - Linear is a modern issue tracking and project planning tool for fast-moving teams. It helps streamline workflows, organize projects, and boost productivity.
- [Jira](https://composio.dev/toolkits/jira) - Jira is Atlassian’s platform for bug tracking, issue tracking, and agile project management. It helps teams organize work, prioritize tasks, and deliver projects efficiently.
- [Clickup](https://composio.dev/toolkits/clickup) - ClickUp is an all-in-one productivity platform for managing tasks, docs, goals, and team collaboration. It streamlines project workflows so teams can work smarter and stay organized in one place.
- [Monday](https://composio.dev/toolkits/monday) - Monday.com is a customizable work management platform for project planning and collaboration. It helps teams organize tasks, automate workflows, and track progress in real time.
- [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time.
- [Agiled](https://composio.dev/toolkits/agiled) - Agiled is an all-in-one business management platform for CRM, projects, and finance. It helps you streamline workflows, consolidate client data, and manage business processes in one place.
- [Ascora](https://composio.dev/toolkits/ascora) - Ascora is a cloud-based field service management platform for service businesses. It streamlines scheduling, invoicing, and customer operations in one place.
- [Basecamp](https://composio.dev/toolkits/basecamp) - Basecamp is a project management and team collaboration tool by 37signals. It helps teams organize tasks, share files, and communicate efficiently in one place.
- [Beeminder](https://composio.dev/toolkits/beeminder) - Beeminder is an online goal-tracking platform that uses monetary pledges to keep you motivated. Stay accountable and hit your targets with real financial incentives.
- [Boxhero](https://composio.dev/toolkits/boxhero) - Boxhero is a cloud-based inventory management platform for SMBs, offering real-time updates, barcode scanning, and team collaboration. It helps businesses streamline stock tracking and analytics for smarter inventory decisions.
- [Breathe HR](https://composio.dev/toolkits/breathehr) - Breathe HR is cloud-based HR software for SMEs to manage employee data, absences, and performance. It simplifies HR admin, making it easy to keep employee records accurate and up to date.
- [Breeze](https://composio.dev/toolkits/breeze) - Breeze is a project management platform designed to help teams plan, track, and collaborate on projects. It streamlines workflows and keeps everyone on the same page.
- [Bugherd](https://composio.dev/toolkits/bugherd) - Bugherd is a visual feedback and bug tracking tool for websites. It helps teams and clients report website issues directly on live sites for faster fixes.
- [Canny](https://composio.dev/toolkits/canny) - Canny is a platform for managing customer feedback and feature requests. It helps teams prioritize product decisions based on real user insights.
- [Chmeetings](https://composio.dev/toolkits/chmeetings) - Chmeetings is a church management platform for events, members, donations, and volunteers. It streamlines church operations and improves community engagement.

## Frequently Asked Questions

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

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

### Can I use Tool Router MCP with Vercel AI SDK v6?

Yes, you can. Vercel AI SDK v6 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 Softr tools.

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

Yes, absolutely. You can configure which Softr 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 Softr data and credentials are handled as safely as possible.

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