Bring Rss Reader
to Google ADK
Learn how to connect Inoreader to Google ADK and start using 10 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the 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.
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.
How it works
1. Subscribe to this server
2. Enter your Inoreader Access Token (found in your developer preferences)
3. Start querying and organizing your knowledge base from Claude, Cursor, or any MCP client
Who is this for?
- Researchers & Analysts — aggregate intelligence from hundreds of sources and filter for specific keywords using AI.
- Content Creators — monitor industry trends and save inspiration directly to tagged folders without leaving your workspace.
- Information Junkies — keep your 'Unread' counts at zero by letting your AI assistant help you prioritize what truly matters.
Built-in capabilities (10)
Articles will remain but the organizational label is removed. Delete a tag or folder
Use "user/-/state/com.google/starred" to star/unstar an item. Add or remove tags from articles (e.g., Starred)
Get the number of unread items per feed/folder
Get Inoreader user information
Use "user/-/state/com.google/reading-list" for all items. Get articles for a specific feed, folder, or tag
List all user subscriptions (feeds)
List all user tags and folders
Mark all items in a stream as read
Subscribe to a new feed by URL
Rename an existing tag or folder
Why Google ADK?
Google ADK natively supports Inoreader as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 10 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.
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Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution
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Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with Inoreader
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Production-ready features like session management, evaluation, and deployment come built-in. not bolted on
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Seamless integration with Google Cloud services means you can combine Inoreader tools with BigQuery, Vertex AI, and Cloud Functions
Inoreader in Google ADK
Inoreader and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Inoreader to Google ADK 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.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 3,400+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Inoreader in Google ADK
The Inoreader 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 Google ADK 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.
* 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
How Vinkius secures
Inoreader for Google ADK
Every tool call from Google ADK to the Inoreader MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I use this to find specific articles across all my subscriptions?
Yes! Use the list_stream_contents tool with the system stream ID user/-/state/com.google/reading-list. You can then ask the AI to filter or search for specific keywords within the returned articles.
Is it possible to star articles directly from the conversation?
Absolutely. Use the edit_tag tool and provide the Article ID with the add parameter set to user/-/state/com.google/starred. This will instantly save the article to your Starred folder in Inoreader.
How do I see how many unread articles I have in each folder?
Run the get_unread_counts tool. It returns a structured list of all your streams (feeds, folders, and tags) along with the precise count of unread items for each.
How does Google ADK connect to MCP servers?
Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.
Can ADK agents use multiple MCP servers?
Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.
Which Gemini models work best with MCP tools?
Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.
McpToolset not found
Update: pip install --upgrade google-adk