How to integrate Semanticscholar MCP with Claude Agent SDK

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Introduction

This guide walks you through connecting Semanticscholar to the Claude Agent SDK using the Composio tool router. By the end, you'll have a working Semanticscholar agent that can find the latest papers on graph neural networks, list citations for a specific research paper, summarize an author’s recent publications, get references cited by a given paper through natural language commands.

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

What is Claude Agent SDK?

The Claude Agent SDK is Anthropic's official framework for building AI agents powered by Claude. It provides a streamlined interface for creating agents with MCP tool support and conversation management.

Key features include:

  • Native MCP Support: Built-in support for Model Context Protocol servers
  • Permission Modes: Control tool execution permissions
  • Streaming Responses: Real-time response streaming for interactive applications
  • Context Manager: Clean async context management for sessions

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

The Semanticscholar MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Semantic Scholar account. It provides structured and secure access to scholarly data, so your agent can search for academic papers, retrieve detailed author profiles, analyze citations, and explore references or publication histories on your behalf.

  • Comprehensive literature search and discovery: Let your agent search for academic papers by topic, author, or relevance and retrieve lists of matching publications with rich metadata.
  • In-depth paper and author insights: Ask your agent to fetch detailed information about specific papers—including titles, abstracts, authors, and publication years—or get complete profiles for researchers and their entire body of work.
  • Citation and reference analysis: Enable your agent to trace the impact of a paper by pulling its citations or explore the foundational research it builds upon by listing its references.
  • Batch retrieval for large-scale research: Efficiently gather details on multiple papers or authors at once, streamlining reviews and bibliometric analyses across large datasets.
  • Bulk and relevance-based queries: Use advanced bulk search and filtering to identify up to thousands of papers at a time, making it easy for your agent to support systematic literature reviews and academic data exploration.

Supported Tools & Triggers

Tools
Details about an authorExamples: https://api.
Details about an author s papersRetrieves a list of papers authored by a specific researcher identified by their unique semantic scholar author id.
Details about a paperExamples: https://api.
Details about a paper s authorsRetrieves the list of authors for a specific paper identified by its unique paper id in the semantic scholar database.
Details about a paper s citationsRetrieves a list of citations for a specific academic paper using its unique semantic scholar paper id.
Details about a paper s referencesRetrieves the list of references cited by a specific paper in the semantic scholar database.
Get details for multiple authors at onceRetrieves detailed information for multiple authors from semantic scholar in a single api call.
Get details for multiple papers at onceThe semanticscholar paper batch endpoint allows users to retrieve data for multiple academic papers in a single api call.
Paper bulk searchBehaves similarly to /paper/search, but is intended for bulk retrieval of basic paper data without search relevance: text query is optional and supports boolean logic for document matching.
Paper relevance searchThe searchpapers endpoint allows users to search for academic papers within the semantic scholar database.
Paper title searchBehaves similarly to /paper/search, but is intended for retrieval of a single paper based on closest title match to given query.
Search for authors by nameThe authorsearch endpoint allows users to search for authors within the semantic scholar database.
Suggest paper query completionsTo support interactive query-completion, return minimal information about papers matching a partial query example: https://api.
Text snippet searchReturn the text snippets that most closely match the query.

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 Claude/Anthropic API Key
  • Primary know-how of Claude Agents SDK
  • A Semanticscholar account
  • Some knowledge of Python

Getting API Keys for Claude/Anthropic and Composio

Claude/Anthropic API Key
  • Go to the Anthropic Console and create an API key. You'll need credits to use the models.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.

Install dependencies

pip install composio-anthropic claude-agent-sdk python-dotenv

Install the Composio SDK and the Claude Agents SDK.

What's happening:

  • composio-anthropic provides Composio integration for Anthropic
  • claude-agent-sdk is the core agent framework
  • python-dotenv loads environment variables

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
ANTHROPIC_API_KEY=your_anthropic_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID identifies the user for session management
  • ANTHROPIC_API_KEY authenticates with Anthropic/Claude

Import dependencies

import asyncio
from claude_agent_sdk import ClaudeSDKClient, ClaudeAgentOptions
import os
from composio import Composio
from dotenv import load_dotenv

load_dotenv()
What's happening:
  • We're importing all necessary libraries including the Claude Agent SDK and Composio
  • The load_dotenv() function loads environment variables from your .env file
  • This setup prepares the foundation for connecting Claude with Semanticscholar functionality

Create a Composio instance and Tool Router session

async def chat_with_remote_mcp():
    api_key = os.getenv("COMPOSIO_API_KEY")
    if not api_key:
        raise RuntimeError("COMPOSIO_API_KEY is not set")

    composio = Composio(api_key=api_key)

    # Create Tool Router session for Semanticscholar
    mcp_server = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["semanticscholar"]
    )

    url = mcp_server.mcp.url

    if not url:
        raise ValueError("Session URL not found")
What's happening:
  • The function checks for the required COMPOSIO_API_KEY environment variable
  • We're creating a Composio instance using our API key
  • The create method creates a Tool Router session for Semanticscholar
  • The returned url is the MCP server URL that your agent will use

Configure Claude Agent with MCP

# Configure remote MCP server for Claude
options = ClaudeAgentOptions(
    permission_mode="bypassPermissions",
    mcp_servers={
        "composio": {
            "type": "http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    },
    system_prompt="You are a helpful assistant with access to Semanticscholar tools via Composio.",
    max_turns=10
)
What's happening:
  • We're configuring the Claude Agent options with the MCP server URL
  • permission_mode="bypassPermissions" allows the agent to execute operations without asking for permission each time
  • The system prompt instructs the agent that it has access to Semanticscholar
  • max_turns=10 limits the conversation length to prevent excessive API usage

Create client and start chat loop

# Create client with context manager
async with ClaudeSDKClient(options=options) as client:
    print("\nChat started. Type 'exit' or 'quit' to end.\n")

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

        # Send query
        await client.query(user_input)

        # Receive and print response
        print("Claude: ", end="", flush=True)
        async for message in client.receive_response():
            if hasattr(message, "content"):
                for block in message.content:
                    if hasattr(block, "text"):
                        print(block.text, end="", flush=True)
        print()
What's happening:
  • The Claude SDK client is created using the async context manager pattern
  • The agent processes each query and streams the response back in real-time
  • The chat loop continues until the user types 'exit' or 'quit'

Run the application

if __name__ == "__main__":
    asyncio.run(chat_with_remote_mcp())
What's happening:
  • This entry point runs the async chat_with_remote_mcp() function using asyncio.run()
  • The application will start, create the MCP connection, and begin the interactive chat session

Complete Code

Here's the complete code to get you started with Semanticscholar and Claude Agent SDK:

import asyncio
from claude_agent_sdk import ClaudeSDKClient, ClaudeAgentOptions
import os
from composio import Composio
from dotenv import load_dotenv

load_dotenv()

async def chat_with_remote_mcp():
    api_key = os.getenv("COMPOSIO_API_KEY")
    if not api_key:
        raise RuntimeError("COMPOSIO_API_KEY is not set")

    composio = Composio(api_key=api_key)

    # Create Tool Router session for Semanticscholar
    mcp_server = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["semanticscholar"]
    )

    url = mcp_server.mcp.url

    if not url:
        raise ValueError("Session URL not found")

    # Configure remote MCP server for Claude
    options = ClaudeAgentOptions(
        permission_mode="bypassPermissions",
        mcp_servers={
            "composio": {
                "type": "http",
                "url": url,
                "headers": {
                    "x-api-key": os.getenv("COMPOSIO_API_KEY")
                }
            }
        },
        system_prompt="You are a helpful assistant with access to Semanticscholar tools via Composio.",
        max_turns=10
    )

    # Create client with context manager
    async with ClaudeSDKClient(options=options) as client:
        print("\nChat started. Type 'exit' or 'quit' to end.\n")

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

            # Send query
            await client.query(user_input)

            # Receive and print response
            print("Claude: ", end="", flush=True)
            async for message in client.receive_response():
                if hasattr(message, "content"):
                    for block in message.content:
                        if hasattr(block, "text"):
                            print(block.text, end="", flush=True)
            print()

if __name__ == "__main__":
    asyncio.run(chat_with_remote_mcp())

Conclusion

You've successfully built a Claude Agent SDK agent that can interact with Semanticscholar through Composio's Tool Router.

Key features:

  • Native MCP support through Claude's agent framework
  • Streaming responses for real-time interaction
  • Permission bypass for smooth automated workflows
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

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FAQ

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

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

Can I use Tool Router MCP with Claude Agent SDK?

Yes, you can. Claude Agent 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 Semanticscholar tools.

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

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

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