How to Use the Inoreader MCP in Pydantic AI

Q: How does Pydantic AI validate Inoreader API responses?

The Pydantic AI framework wraps the listsubscriptions tool output in runtime models. If the Inoreader API returns unexpected fields, Pydantic AI raises a validation error immediately.

Q: Can Pydantic AI clean up my unread queue in Inoreader?

Yes, your Pydantic AI agent calls markallasread to clear out processed Inoreader items. The Pydantic AI framework validates the success state returned by the server to confirm the Inoreader queue is empty.

Q: How do I register the Inoreader MCP Server in Pydantic AI?

You instantiate MCPToolset with your Vinkius HTTP URL and pass it to your Pydantic AI Agent's toolsets list. The 10 Inoreader tools like getuserinfo are registered with runtime validation schemas automatically.

Q: Can Pydantic AI rename Inoreader folders safely?

Yes, renametag modifies your Inoreader folder names while validating that both the old and new tag names are non-empty strings. This prevents accidental empty folder names in your Inoreader account during Pydantic AI runs.

Run type-safe Inoreader RSS pipelines with Pydantic AI to guarantee structured, validated feed data at runtime.

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Connect Inoreader MCP to Pydantic AI

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Setup Inoreader with Pydantic AI

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Type-safe Inoreader stream extraction in Pydantic AI

The `list_stream_contents` tool returns Inoreader RSS article data that Pydantic AI validates against strict runtime schemas. If an Inoreader feed contains malformed HTML or missing author fields, the Pydantic AI framework catches it instantly instead of passing corrupt data to your LLM. This strict validation ensures your Pydantic AI Inoreader data pipeline remains clean. Your Pydantic AI agent can safely parse thousands of Inoreader articles, knowing that any schema drift in the RSS source will trigger an immediate, traceable error.

Structured Inoreader tag management via MCP Server

The `list_tags` tool retrieves your Inoreader folder structure and converts it into strongly typed Pydantic AI objects. Your Pydantic AI agent uses this structured list to decide exactly where to route incoming Inoreader articles. When moving items, the Pydantic AI agent calls `edit_tag` to apply Inoreader labels. Because the MCP Server enforces type safety, you never have to worry about passing malformed tag strings or empty IDs to the Inoreader API from Pydantic AI.

Validated Inoreader subscription workflows in Pydantic AI

The `quick_add_subscription` tool allows your Pydantic AI agent to subscribe to new Inoreader feeds while enforcing strict URL patterns. Pydantic AI validates the target Inoreader URL format before the tool ever communicates with the API. After subscribing, the Pydantic AI agent runs `get_unread_counts` to verify the Inoreader feed is active and returning integer counts. This prevents your Pydantic AI system from tracking dead or broken Inoreader RSS endpoints.

Setup guide

Set up Inoreader MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "inoreader-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Inoreader tools.",
)

result = await agent.run("List recent Inoreader transactions")
print(result.output)

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Common questions about Inoreader MCP in Pydantic AI

The Pydantic AI framework wraps the `list_subscriptions` tool output in runtime models. If the Inoreader API returns unexpected fields, Pydantic AI raises a validation error immediately.

Yes, your Pydantic AI agent calls `mark_all_as_read` to clear out processed Inoreader items. The Pydantic AI framework validates the success state returned by the server to confirm the Inoreader queue is empty.

You instantiate `MCPToolset` with your Vinkius HTTP URL and pass it to your Pydantic AI Agent's `toolsets` list. The 10 Inoreader tools like `get_user_info` are registered with runtime validation schemas automatically.

Yes, `rename_tag` modifies your Inoreader folder names while validating that both the old and new tag names are non-empty strings. This prevents accidental empty folder names in your Inoreader account during Pydantic AI runs.

Yes, Vinkius handles your Inoreader API credentials inside isolated V8 sandboxes. Your Inoreader RSS subscriptions, tags, and read states are processed in-memory and never cached or logged on external MCP servers during Pydantic AI runs.

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