How to integrate Affinda MCP with Mastra AI

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Introduction

This guide walks you through connecting Affinda to Mastra AI using the Composio tool router. By the end, you'll have a working Affinda agent that can extract invoice data from uploaded pdf, delete a document no longer needed, create a new tag for hr documents, set up webhook for document parsing events through natural language commands.

This guide will help you understand how to give your Mastra AI agent real control over a Affinda account through Composio's Affinda MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

TL;DR

Here's what you'll learn:
  • Set up your environment so Mastra, OpenAI, and Composio work together
  • Create a Tool Router session in Composio that exposes Affinda tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch Affinda tool definitions and attach them as a toolset
  • Build a Mastra agent that can reason, call tools, and return structured results
  • Run an interactive CLI where you can chat with your Affinda agent

What is Mastra AI?

Mastra AI is a TypeScript framework for building AI agents with tool support. It provides a clean API for creating agents that can use external services through MCP.

Key features include:

  • MCP Client: Built-in support for Model Context Protocol servers
  • Toolsets: Organize tools into logical groups
  • Step Callbacks: Monitor and debug agent execution
  • OpenAI Integration: Works with OpenAI models via @ai-sdk/openai

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

The Affinda MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Affinda account. It provides structured and secure access to your document processing workflows, so your agent can upload files, extract data, organize workspaces, label documents, and automate annotation management on your behalf.

  • AI-powered document upload and extraction: Instantly have your agent upload new documents for parsing and extract structured data from various formats using Affinda's advanced AI models.
  • Workspace and collection management: Let your agent create, group, and organize documents into collections and workspaces, keeping your document processing streamlined and organized.
  • Automated annotation updates: Empower your agent to batch update or modify multiple document annotations in a single request, saving you time on manual corrections.
  • Document tagging and organization: Direct your agent to create tags and label documents, making it easy to categorize and quickly retrieve important files.
  • Effortless cleanup and resource management: Have your agent delete unwanted documents or collections, ensuring your Affinda account stays tidy and relevant at all times.

Supported Tools & Triggers

Tools
Batch Update AnnotationsTool to update multiple annotations in one request.
Create CollectionTool to create a new collection.
Create DocumentTool to upload a new document for parsing.
Create OrganizationTool to create a new organization.
Create RESTHook SubscriptionTool to create a new resthook subscription.
Create TagTool to create a new tag.
Create Validation ResultTool to create a validation result.
Create WorkspaceTool to create a new workspace.
Delete CollectionTool to delete a specific collection by its id.
Delete DocumentTool to delete a specific document by its id.
Delete OrganizationTool to delete a specific organization by its id.
Delete Resthook SubscriptionTool to delete a specific resthook subscription by id.
Delete WorkspaceTool to delete a specific workspace by its id.
Delete Workspace MembershipTool to remove a user from a workspace by membership id.
Get TagsTool to list all tags.
Get All Validation ResultsTool to list validation results for documents.
Get Workspace MembershipsTool to list all workspace memberships for the authenticated user.
Get AnnotationsTool to retrieve a list of all annotations.
Get CollectionTool to retrieve details of a specific collection by its id.
Get CollectionsTool to retrieve a list of all collections.
Get DocumentTool to retrieve details of a specific document by its id.
Get DocumentsTool to retrieve a list of all documents.
Get Document TypeTool to retrieve details of a specific document type by its id.
Get Document TypesTool to retrieve a list of all document types.
Get ExtractorsTool to retrieve a list of all extractors.
Get OrganizationTool to retrieve details of a specific organization by its id.
Get OrganizationsTool to retrieve a list of all organizations.
Get Resthook SubscriptionTool to retrieve details of a specific resthook subscription by its id.
Get RESTHook SubscriptionsTool to retrieve a list of all resthook subscriptions.
Get Usage by WorkspaceTool to retrieve monthly credits consumption for a workspace.
Get WorkspaceTool to retrieve details of a specific workspace by its id.
Get Workspace MembershipTool to retrieve details of a specific workspace membership by its id.
Get WorkspacesTool to retrieve a list of all workspaces.
Update CollectionTool to update specific fields of a collection.
Update DocumentTool to update specific fields of a document.
Update Document DataTool to update parsed data for a resume or job description document.
Update OrganizationTool to update specific fields of an organization.
Update RESTHook SubscriptionTool to update an existing resthook subscription.
Update WorkspaceTool to update specific fields of a workspace.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

Before starting, make sure you have:
  • Node.js 18 or higher
  • A Composio account with an active API key
  • An OpenAI API key
  • Basic familiarity with TypeScript

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key.
  • You need credits or a connected billing setup to use the models.
  • Store the key somewhere safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Go to Settings and copy your API key.
  • This key lets your Mastra agent talk to Composio and reach Affinda through MCP.

Install dependencies

bash
npm install @composio/core @mastra/core @mastra/mcp @ai-sdk/openai dotenv

Install the required packages.

What's happening:

  • @composio/core is the Composio SDK for creating MCP sessions
  • @mastra/core provides the Agent class
  • @mastra/mcp is Mastra's MCP client
  • @ai-sdk/openai is the model wrapper for OpenAI
  • dotenv loads environment variables from .env

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your requests to Composio
  • COMPOSIO_USER_ID tells Composio which user this session belongs to
  • OPENAI_API_KEY lets the Mastra agent call OpenAI models

Import libraries and validate environment

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

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

if (!openaiAPIKey) 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 as string,
});
What's happening:
  • dotenv/config auto loads your .env so process.env.* is available
  • openai gives you a Mastra compatible model wrapper
  • Agent is the Mastra agent that will call tools and produce answers
  • MCPClient connects Mastra to your Composio MCP server
  • Composio is used to create a Tool Router session

Create a Tool Router session for Affinda

typescript
async function main() {
  const session = await composio.create(
    composioUserID as string,
    {
      toolkits: ["affinda"],
    },
  );

  const composioMCPUrl = session.mcp.url;
  console.log("Affinda MCP URL:", composioMCPUrl);
What's happening:
  • create spins up a short-lived MCP HTTP endpoint for this user
  • The toolkits array contains "affinda" for Affinda access
  • session.mcp.url is the MCP URL that Mastra's MCPClient will connect to

Configure Mastra MCP client and fetch tools

typescript
const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      nasdaq: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

console.log("Fetching MCP tools from Composio...");
const composioTools = await mcpClient.getTools();
console.log("Number of tools:", Object.keys(composioTools).length);
What's happening:
  • MCPClient takes an id for this client and a list of MCP servers
  • The headers property includes the x-api-key for authentication
  • getTools fetches the tool definitions exposed by the Affinda toolkit

Create the Mastra agent

typescript
const agent = new Agent({
    name: "affinda-mastra-agent",
    instructions: "You are an AI agent with Affinda tools via Composio.",
    model: "openai/gpt-5",
  });
What's happening:
  • Agent is the core Mastra agent
  • name is just an identifier for logging and debugging
  • instructions guide the agent to use tools instead of only answering in natural language
  • model uses openai("gpt-5") to configure the underlying LLM

Set up interactive chat interface

typescript
let messages: AiMessageType[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end.\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({
    id: crypto.randomUUID(),
    role: "user",
    content: trimmedInput,
  });

  console.log("\nAgent is thinking...\n");

  try {
    const response = await agent.generate(messages, {
      toolsets: {
        affinda: composioTools,
      },
      maxSteps: 8,
    });

    const { text } = response;

    if (text && text.trim().length > 0) {
      console.log(`Agent: ${text}\n`);
        messages.push({
          id: crypto.randomUUID(),
          role: "assistant",
          content: text,
        });
      }
    } catch (error) {
      console.error("\nError:", error);
    }

    rl.prompt();
  });

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

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});
What's happening:
  • messages keeps the full conversation history in Mastra's expected format
  • agent.generate runs the agent with conversation history and Affinda toolsets
  • maxSteps limits how many tool calls the agent can take in a single run
  • onStepFinish is a hook that prints intermediate steps for debugging

Complete Code

Here's the complete code to get you started with Affinda and Mastra AI:

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

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

if (!openaiAPIKey) 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 as string });

async function main() {
  const session = await composio.create(composioUserID as string, {
    toolkits: ["affinda"],
  });

  const composioMCPUrl = session.mcp.url;

  const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      affinda: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "affinda-mastra-agent",
    instructions: "You are an AI agent with Affinda tools via Composio.",
    model: "openai/gpt-5",
  });

  let messages: AiMessageType[] = [];

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

  rl.prompt();

  rl.on("line", async (input: string) => {
    const trimmed = input.trim();
    if (["exit", "quit"].includes(trimmed.toLowerCase())) {
      rl.close();
      return;
    }

    messages.push({ id: crypto.randomUUID(), role: "user", content: trimmed });

    const { text } = await agent.generate(messages, {
      toolsets: { affinda: composioTools },
      maxSteps: 8,
    });

    if (text) {
      console.log(`Agent: ${text}\n`);
      messages.push({ id: crypto.randomUUID(), role: "assistant", content: text });
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main();

Conclusion

You've built a Mastra AI agent that can interact with Affinda through Composio's Tool Router. You can extend this further by:
  • Adding other toolkits like Gmail, Slack, or GitHub
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows

How to build Affinda MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Affinda MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Affinda MCP with Claude Agent SDK

Google ADK

Google ADK

Use Affinda MCP with Google ADK

LangChain

LangChain

Use Affinda MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Affinda MCP with Vercel AI SDK

LlamaIndex

LlamaIndex

Use Affinda MCP with LlamaIndex

CrewAI

CrewAI

Use Affinda MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Affinda MCP?

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

Can I use Tool Router MCP with Mastra AI?

Yes, you can. Mastra AI 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 Affinda tools.

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

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

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