3,400+ MCP servers ready to use
Vinkius

Bring Rss Aggregator
to CrewAI

Learn how to connect Feedly to CrewAI and start using 10 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.

Get Article DetailsGet Feed MetadataGet Stream ContentsGet User ProfileList CategoriesList SubscriptionsList TagsMark Articles As ReadSubscribe To FeedUnsubscribe From Feed

What is the Feedly MCP Server?

Connect your Feedly account to any AI agent and take full control of your news aggregation and content curation workflows through natural conversation.

What you can do

  • Feed Orchestration — List and manage your subscribed news sources programmatically, including adding or removing RSS/Atom feeds
  • Stream Intelligence — Retrieve the latest entries (articles) from specific feeds or categories and monitor unread counts in real-time
  • Content Extraction — Programmatically fetch complete article text and metadata to perform deep analysis and summaries via your agent
  • Organization Control — Manage your Feedly categories and personal tags to maintain a structured and high-fidelity reading environment
  • Reading Workflow — Mark articles as read and manage your reading list programmatically to streamline your news consumption

How it works

1. Subscribe to this server
2. Retrieve your Developer Access Token from Feedly (Settings > Integrations > Developer Token)
3. Start managing your news curation from Claude, Cursor, or any MCP client

No more manual scrolling through endless articles. Your AI acts as your dedicated news analyst and content curator.

Who is this for?

  • Market Researchers — instantly track industry news and retrieve full article contents for deep analysis using natural language
  • Content Strategists — monitor trending topics across specific feeds and manage curation tags without leaving your workspace
  • Busy Professionals — automate the process of marking articles as read and summarizing daily highlights through simple AI queries

Built-in capabilities (10)

get_article_details

Get full content of an article

get_feed_metadata

Get metadata for a specific feed

get_stream_contents

Retrieve articles from a stream

get_user_profile

Get your Feedly profile

list_categories

List your Feedly categories

list_subscriptions

List all subscribed feeds

list_tags

List your personal tags

mark_articles_as_read

Mark one or more articles as read

subscribe_to_feed

Follow a new news source

unsubscribe_from_feed

Stop following a news source

Why CrewAI?

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

  • 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

See it in action

Feedly in CrewAI

AI AgentVinkius
High Security·Kill Switch·Plug and Play
Why Vinkius

Feedly and 3,400+ other MCP servers. One platform. One governance layer.

Teams that connect Feedly to CrewAI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.

3,400+MCP Servers ready
<40msCold start
60%Token savings
Raw MCP
Vinkius
Server catalogFind and host yourself3,400+ managed
InfrastructureSelf-hostedSandboxed V8 isolates
Credential handlingPlaintext in configVault + runtime injection
Data loss preventionNoneConfigurable DLP policies
Kill switchNoneGlobal instant shutdown
Financial circuit breakersNonePer-server limits + alerts
Audit trailNoneEd25519 signed logs
SIEM log streamingNoneSplunk, Datadog, Webhook
HoneytokensNoneCanary alerts on leak
Custom domainsNot applicableDNS challenge verified
GDPR complianceManual effortAutomated purge + export
Enterprise Security

Why teams choose Vinkius for Feedly in CrewAI

The Feedly 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. All 10 tools execute in hardened sandboxes optimized for native MCP execution.

Your AI agents in CrewAI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.

Feedly
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

The Vinkius Advantage

How Vinkius secures Feedly for CrewAI

Every tool call from CrewAI to the Feedly MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.

< 40msCold start
Ed25519Signed audit chain
60%Token savings
FAQ

Frequently asked questions

01

How do I get a Feedly Developer Token?

Log in to Feedly, go to your account settings, navigate to Integrations, and select 'Developer Token' to request your access key.

02

Can the agent mark articles as read automatically?

Yes! Use the mark_articles_as_read tool and provide an array of article IDs to clear them from your unread list programmatically.

03

How many articles can I retrieve at once?

The get_stream_contents tool allows you to specify a count (default 20, max 1000) for retrieving articles from a stream.

04

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.

05

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.

06

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.

07

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.

08

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.

09

MCP tools not discovered

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

10

Agent not using tools

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

11

Timeout errors

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

12

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.