3,400+ MCP servers ready to use
Vinkius

Inoreader MCP Server for CrewAIGive CrewAI instant access to 10 tools to Delete Tag, Edit Tag, Get Unread Counts, and more

Built by Vinkius GDPR 10 Tools Framework

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

Ask AI about this App Connector for CrewAI

The Inoreader app connector for CrewAI is a standout in the Productivity category — giving your AI agent 10 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python
from crewai import Agent, Task, Crew

agent = Agent(
    role="Inoreader Specialist",
    goal="Help users interact with Inoreader effectively",
    backstory=(
        "You are an expert at leveraging Inoreader 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 Inoreader "
        "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)
Inoreader
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Inoreader MCP Server

Connect your Inoreader account to any AI agent and transform how you monitor news, blogs, and social feeds through natural language control.

When paired with CrewAI, Inoreader becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Inoreader 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

  • Feed Management — List all your subscriptions and quickly add new RSS/Atom feeds by URL.
  • Content Extraction — Fetch article contents from specific feeds, folders, or system streams with advanced filtering.
  • Organization — List, create, rename, and delete tags or folders to keep your information architecture clean.
  • Engagement — Star important articles, mark items as read, or batch-clear entire streams instantly.
  • Unread Monitoring — Get real-time summaries of unread counts across all your categorized content.

The Inoreader MCP Server exposes 10 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 10 Inoreader tools available for CrewAI

When CrewAI connects to Inoreader through Vinkius, your AI agent gets direct access to every tool listed below — spanning rss-reader, content-curation, news-monitoring, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

delete_tag

Articles will remain but the organizational label is removed. Delete a tag or folder

edit_tag

Use "user/-/state/com.google/starred" to star/unstar an item. Add or remove tags from articles (e.g., Starred)

get_unread_counts

Get the number of unread items per feed/folder

get_user_info

Get Inoreader user information

list_stream_contents

Use "user/-/state/com.google/reading-list" for all items. Get articles for a specific feed, folder, or tag

list_subscriptions

List all user subscriptions (feeds)

list_tags

List all user tags and folders

mark_all_as_read

Mark all items in a stream as read

quick_add_subscription

Subscribe to a new feed by URL

rename_tag

Rename an existing tag or folder

Connect Inoreader to CrewAI via MCP

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

01

Install CrewAI

Run pip install crewai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
03

Customize the agent

Adjust the role, goal, and backstory to fit your use case
04

Run the crew

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

Why Use CrewAI with the Inoreader MCP Server

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

01

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

02

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

03

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

04

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

Inoreader + CrewAI Use Cases

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

01

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

02

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

03

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

04

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

Example Prompts for Inoreader in CrewAI

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

01

"What are the latest news from my Tech folder?"

02

"Find articles about 'SpaceX' that I haven't read yet."

03

"Mark all articles in my 'Social Media' tag as read."

Troubleshooting Inoreader MCP Server with CrewAI

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

01

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.
02

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".
03

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.
04

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.

Inoreader + CrewAI FAQ

Common questions about integrating Inoreader MCP Server with CrewAI.

01

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.
02

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.
03

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.
04

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.
05

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.