MCP Servers · glidea

zenfeed

Zenfeed is an AI-powered RSS reader and information aggregation platform written in Go that combines traditional RSS feeds with LLM-based filtering, summarization, and monitoring. It integrates with multiple AI providers (Qwen, OpenAI, Anthropic, Gemini, Deepseek) and supports email notifications, webhooks, and MCP server functionality.

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Source: GitHub — github.com/glidea/zenfeed

1.7k

GitHub stars

105

Forks

Primary language

AGPL-3.0

License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

Field	Value
Repository	glidea/zenfeed
Owner	glidea
Primary language	Go
License	AGPL-3.0 — OSI-approved
Stars	1.7k
Forks	105
Open issues	14
Latest release	v0.7.0 (2025-11-07)
Last updated	2026-07-03
Source	https://github.com/glidea/zenfeed

What zenfeed is

Built in Go with declarative YAML configuration, Zenfeed implements a pipeline-based content processing model similar to Prometheus relabeling, supports custom prompts for tagging/filtering, exports RSS and query APIs, and can operate as an MCP server for AI tool integration. Deployable via Docker Compose with PostgreSQL backend.

Quickstart

Get the zenfeed source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/glidea/zenfeed.git2cd zenfeed3# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

AI-Enhanced Information Triage for Knowledge Workers

Replace or augment Feedly AI for teams that need automated feed summarization, smart filtering, and daily digest delivery without algorithmic bias. The pipeline processing model allows custom scoring and classification rules.

Event Monitoring & Alerting System

Replace or supplement specialized monitoring tools (万物追踪, WiseFlow) for tracking specific events/topics across curated RSS sources with AI-driven relevance ranking and webhook notifications to downstream systems.

Private AI Search Engine over Custom Data Sources

Index high-quality RSS feeds as a personal knowledge base with Query API access, enabling context-aware semantic search and conversation via MCP integration with AI chat tools (Cherry Studio, etc.).

Implementation considerations

Requires external LLM API key (Qwen/Silicon Flow recommended for free tier; also supports OpenAI, Anthropic, Gemini, Deepseek). Cost scales with content volume and processing frequency.
Default deployment uses PostgreSQL; ensure persistent volume and backup strategy for production. Data retention policy (8 days default) must align with compliance/business requirements.
Custom YAML configuration is powerful but requires expertise in pipeline design, prompt engineering, and relabeling rules. Expect iteration cycles for optimal filtering/scoring behavior.
Network access to RSS source URLs is mandatory; verify firewall and proxy rules permit outbound HTTP(S) to diverse domains. No built-in rate-limiting or caching optimization documented.
API keys are stored in environment variables with no encryption at rest. Network exposure without authentication is a security risk; restrict to trusted internal networks or add reverse-proxy authentication.

When to avoid it — and what to weigh

Requires Enterprise Authentication & Multi-Tenancy — Zenfeed explicitly lacks authentication mechanisms and is not designed for multi-user/multi-tenant scenarios. Unsuitable for SaaS platforms or organizations requiring fine-grained access control.
Need Guaranteed Long-Term Data Retention — Default data retention is 8 days. If compliance or archival requirements mandate longer storage, custom deployment modifications are necessary and unsupported.
Strict Commercial Use Requirements — AGPLv3 license requires any distribution, modification, or network exposure to remain open-source. Commercial deployment without open-sourcing derivative work violates license. Author requests notification for commercial use but enforcement is unclear.
Zero-Configuration, Fully Managed SaaS Expectations — This is self-hosted software requiring API key provisioning, Docker knowledge, and configuration management. Not a plug-and-play managed service.

License & commercial use

AGPLv3 (GNU Affero General Public License v3.0). Copyleft license: any modification, distribution, or network service use must release source code publicly under the same license. Not a permissive license (e.g., MIT, Apache 2.0).

Requires review and author contact. README states 'commercial use should contact author for notification; can provide support within reasonable scope.' AGPLv3 does not automatically permit commercial use without open-sourcing. No SLA, indemnification, or commercial support terms documented. Explicitly discourages 'gray industry' use. Recommend legal review before commercial deployment.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

Signal	Assessment
Maintenance	Active
Documentation	Adequate
License clarity	Needs review
Deployment complexity	Moderate
DEV.co fit	Good
Assessment confidence	High

Security considerations

No built-in authentication or authorization. API keys exposed in environment variables with no encryption at rest. Designed for private/internal deployment only. README explicitly warns against public internet exposure without reverse-proxy protection. No security audit, SBOM, or vulnerability disclosure process documented. User responsible for network isolation, API key rotation, and HTTPS termination at reverse proxy layer.

Alternatives to consider

Feedly AI

Managed SaaS RSS reader with built-in AI summarization. No self-hosting required, but proprietary, closed-source, and less customizable. Suitable if you prioritize ease-of-use over control and open-source philosophy.

WiseFlow (AI Chief Intelligence Officer)

Similar event-monitoring/information-tracking focus. More opinionated for AI research use cases. Requires external LLM API like Zenfeed. Choose WiseFlow if you need web scraping and broader data source support; Zenfeed if you prefer RSS-centric, pipeline-based architecture.

RSSHub + Custom Aggregator

RSSHub generates RSS feeds from any web source; combine with simple aggregator (Miniflux, Tiny Tiny RSS). More modular, lighter-weight, no AI baked in. Better if you need pure RSS without LLM processing or prefer decoupled components.

Software development agency

Build on zenfeed with DEV.co software developers

Zenfeed gives you the power of AI-driven feed curation without algorithmic manipulation. Deploy in 1 minute with Docker, connect your LLM API, and start filtering feeds the way you want. Evaluate for team information triage, event monitoring, or personal knowledge management.

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zenfeed FAQ

Can I use Zenfeed for commercial purposes?

AGPLv3 requires source code to be released. Author requests notification and may grant exceptions 'within reasonable scope,' but no formal commercial license exists. Requires author contact and legal review before commercial deployment. Not recommended for commercial SaaS without clarification.

What LLM providers are supported?

Default is Qwen (Silicon Flow). Also supports OpenAI, Anthropic Claude, Google Gemini, and Deepseek. Custom endpoints via API configuration. Each has different pricing and rate limits; Silicon Flow is recommended for free tier.

How long is data retained?

Default retention is 8 days. Configurable via YAML. Data not permanently stored. If longer retention is required for compliance, custom deployment and configuration necessary.

Is there a managed/hosted version of Zenfeed?

No. Zenfeed is self-hosted only. You must run it yourself via Docker Compose or custom deployment. No official SaaS offering or managed hosting partner documented.

Software developers & web developers for hire

DEV.co helps companies turn open-source tools like zenfeed into production software. Our software development services cover the full lifecycle — architecture, web development, integration, and maintenance — delivered by software developers and web developers who ship. Engage our software development agency to implement or customize it for your mcp servers stack.

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