Scopus MCP Server for CrewAIGive CrewAI instant access to 10 tools to Get Abstract, Get Affiliation, Get Author, and more

Name: Scopus
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

Connect your CrewAI agents to Scopus through Vinkius, pass the Edge URL in the `mcps` parameter and every Scopus tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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The Scopus MCP Server for CrewAI is a standout in the Knowledge Management category — giving your AI agent 10 tools to work with, ready to go from day one.

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Scopus Specialist",
    goal="Help users interact with Scopus effectively",
    backstory=(
        "You are an expert at leveraging Scopus tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Scopus "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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About Scopus MCP Server

Connect your Scopus API credentials to any AI agent and unlock the power of Elsevier's massive research database through natural conversation.

When paired with CrewAI, Scopus becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Scopus tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Advanced Search — Query Scopus abstracts and metadata using Boolean syntax and field codes like TITLE-ABS-KEY() or PUBYEAR
Author & Institution Profiles — Retrieve detailed profiles, including H-index, affiliation history, and publication lists
Citation Metrics — Get comprehensive citation overviews, counts, and summaries by year for any document via DOI or Scopus ID
Journal Insights — Access metadata for serials including CiteScore, SJR, and SNIP metrics to evaluate publication impact
PlumX Metrics — Inspect social media mentions, usage, and altmetrics to understand the broader reach of scientific work

The Scopus MCP Server exposes 10 tools through the Vinkius. Connect it to CrewAI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 10 Scopus tools available for CrewAI

When CrewAI connects to Scopus through Vinkius, your AI agent gets direct access to every tool listed below — spanning academic-literature, citation-database, research-metrics, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

get

Get abstract on Scopus

Get detailed metadata for a specific document

get

Get affiliation on Scopus

Get detailed profile for an institution

get

Get author on Scopus

Get detailed profile for a specific author

get

Get citation count on Scopus

Get abstract citation count

get

Get citation overview on Scopus

Get citation counts and summaries by year

get

Get plumx metrics on Scopus

Get Altmetrics for Scopus documents

get

Get serial title on Scopus

Get metadata about journals (metrics like CiteScore, SJR, SNIP)

Search affiliation on Scopus

Search Scopus institutional profiles

Search author on Scopus

Search Scopus author profiles

Search scopus on Scopus

Search Scopus abstracts and metadata

Connect Scopus to CrewAI via MCP

Follow these steps to wire Scopus into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 10 tools from Scopus

Why Use CrewAI with the Scopus MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Scopus through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Scopus + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Scopus MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Scopus for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Scopus, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Scopus tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Scopus against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for Scopus in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Scopus immediately.

"Search Scopus for papers about 'Large Language Models' published in 2024."

"Get the citation overview for DOI 10.1016/j.future.2023.01.001."

"Find the profile and H-index for author ID 7004212771."

Troubleshooting Scopus MCP Server with CrewAI

Common issues when connecting Scopus to CrewAI through Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Scopus + CrewAI FAQ

Common questions about integrating Scopus MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.

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