How to integrate Textrazor MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Textrazor to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Textrazor agent that can extract named entities from this news article, summarize key phrases in customer reviews, classify support tickets by topic automatically, analyze grammatical structure of this sentence through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Textrazor account through Composio's Textrazor 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:
  • Get and set up your OpenAI and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Textrazor
  • Configure an AI agent that can use Textrazor as a tool
  • Run a live chat session where you can ask the agent to perform Textrazor operations

What is open-ai-agents-sdk?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

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

The Textrazor MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Textrazor account. It provides structured and secure access to advanced natural language processing features, so your agent can extract entities, classify content, analyze grammar, and understand relationships within text—all automatically and at scale.

  • Entity and relationship extraction: Enable your agent to identify and classify people, places, organizations, and relationships from any text, powering intelligent content analysis and knowledge graph building.
  • Text classification and categorization: Automatically categorize documents, articles, or snippets using built-in or custom classifiers, making it easy to sort and organize large volumes of text data.
  • Grammatical and dependency analysis: Let your agent parse sentence structure, analyze grammatical relationships, and build dependency trees to support advanced linguistic understanding and text analytics.
  • Custom dictionary and classifier management: Allow the agent to create and update custom entity dictionaries and classifiers, tailoring analysis to specialized domains or business needs.
  • Phrase extraction and sentiment detection: Extract key phrases, multi-word expressions, and even detect logical entailments or word senses, enabling deeper insights from any written content.

Supported Tools & Triggers

Tools
Get Account InformationThis tool retrieves comprehensive information about a textrazor account, providing essential details about the account's status, usage, and limits.
Classify TextThis tool will classify text into predefined categories using textrazor's classification capabilities.
Manage Custom ClassifiersThis tool manages custom classifiers in textrazor, allowing users to create, update, and manage custom classification categories.
Analyze Dependency TreesThe dependencytreesaction analyzes the grammatical relationships between words in text by creating dependency trees.
Dictionary ManagerThe textrazor dictionary manager tool allows users to create, update, and manage custom entity dictionaries in textrazor.
Extract Entailments from TextThis tool extracts entailments from text using textrazor's api.
Extract Named Entities from TextExtract named entities (people, places, companies, etc.
Extract Phrases from TextThe extractphrases action extracts meaningful phrases from input text using textrazor's phrase extraction capability.
Extract Grammatical Relations from TextThis tool extracts grammatical relations between words in the text.
Extract Word SensesThis tool performs word sense disambiguation on the input text by identifying the most likely meanings of words in context.
Spelling CorrectionThis tool performs spelling correction on the provided text using textrazor's deep spelling correction system.
Analyze Content with TextRazorA comprehensive content analysis tool that combines multiple textrazor extractors to perform a complete analysis of the input text.
Extract Topics from TextA tool to extract topics from text using textrazor's topic extraction capabilities.

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:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Textrazor project
  • Some knowledge of Python or Typescript

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard 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

Install dependencies

pip install composio_openai_agents openai-agents python-dotenv

Install the Composio SDK and the OpenAI Agents SDK.

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

Import dependencies

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Textrazor.

Set up the Composio instance

load_dotenv()

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

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
What's happening:
  • load_dotenv() loads your .env file so OPENAI_API_KEY and COMPOSIO_API_KEY are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.

Create a Tool Router session

# Create a Textrazor Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["textrazor"]
)

mcp_url = session.mcp.url

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only textrazor.
  • The router checks the user's Textrazor connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Textrazor.
  • This approach keeps things lightweight and lets the agent request Textrazor tools only when needed during the conversation.

Configure the agent

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Textrazor. "
        "Help users perform Textrazor operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Textrazor and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a HostedMCPTool that connects to the MCP server URL we created earlier.
  • The headers dict includes the Composio API key for secure authentication with the MCP server.
  • require_approval: 'never' means the agent can execute Textrazor operations without asking for permission each time, making interactions smoother.

Start chat loop and handle conversation

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
What's happening:
  • The program prints a session URL that you visit to authorize Textrazor.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using Runner.run().
  • The responses are printed to the console, and conversations are saved locally using SQLite.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Textrazor and open-ai-agents-sdk:

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

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

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["textrazor"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Textrazor. "
        "Help users perform Textrazor operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())

Conclusion

This was a starter code for integrating Textrazor MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Textrazor.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

How to build Textrazor MCP Agent with another framework

Claude Agent SDK

Claude Agent SDK

Use Textrazor MCP with Claude Agent SDK

Google ADK

Google ADK

Use Textrazor MCP with Google ADK

LangChain

LangChain

Use Textrazor MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Textrazor MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Textrazor MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Textrazor MCP with LlamaIndex

CrewAI

CrewAI

Use Textrazor MCP with CrewAI

FAQ

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

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

Can I use Tool Router MCP with OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK 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 Textrazor tools.

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

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

Used by agents from

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Context
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