How do I find my LinkAce API Token?

Log in to your LinkAce dashboard, navigate to User Settings, and generate a new API token from the API section.

What is the Instance URL?

This is the full base URL where your LinkAce instance is hosted, for example: `https://links.yourdomain.com`.

Can I search for specific tags?

While you can search for links by keyword, you can also list all tags to find the specific label IDs used for organization.

LinkAce MCP Server for Pydantic AI 9 tools — connect in under 2 minutes

Name: LinkAce
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 9 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect LinkAce through the Vinkius and every tool is automatically validated against Pydantic schemas — catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to LinkAce "
            "(9 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in LinkAce?"
    )
    print(result.data)

asyncio.run(main())

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* 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 LinkAce MCP Server

Connect your LinkAce instance to any AI agent to automate your personal knowledge base and link archiving. This MCP server enables your agent to add new bookmarks, organize them into lists and tags, and search your entire library directly from natural language interfaces.

Pydantic AI validates every LinkAce tool response against typed schemas, catching data inconsistencies at build time. Connect 9 tools through the Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code — full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Instant Archiving — Quickly add new URLs to your LinkAce library with custom titles and descriptions
Deep Organization — Create and manage tags and lists to keep your bookmarks categorized and easy to find
Semantic Discovery — Search through your entire archived library using keywords via natural language commands
Library Maintenance — Retrieve detailed metadata for specific links or permanently remove outdated bookmarks
Self-Hosted Support — Works with any self-hosted LinkAce instance using your personal API token

The LinkAce MCP Server exposes 9 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect LinkAce to Pydantic AI via MCP

Follow these steps to integrate the LinkAce MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 9 tools from LinkAce with type-safe schemas

Why Use Pydantic AI with the LinkAce MCP Server

Pydantic AI provides unique advantages when paired with LinkAce through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture — switch between OpenAI, Anthropic, or Gemini without changing your LinkAce integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your LinkAce connection logic from agent behavior for testable, maintainable code

LinkAce + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the LinkAce MCP Server delivers measurable value.

Type-safe data pipelines: query LinkAce with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple LinkAce tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query LinkAce and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock LinkAce responses and write comprehensive agent tests

LinkAce MCP Tools for Pydantic AI (9)

These 9 tools become available when you connect LinkAce to Pydantic AI via MCP:

create_new_bookmark

Requires at least a URL. Add a new link to your archive

create_new_collection

Add a new collection (list)

create_new_tag

Add a new tag

delete_bookmark

Remove a bookmark from your archive

get_bookmark_details

Get details for a specific bookmark

list_all_bookmarks

List all bookmarks (links) in your LinkAce account

list_all_collections

List all bookmark collections (lists)

list_all_tags

List all tags used for organizing bookmarks

search_bookmarks

Search for bookmarks by keyword

Example Prompts for LinkAce in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with LinkAce immediately.

"Add 'https://www.wikipedia.org' to my LinkAce bookmarks."

"Search my LinkAce library for 'Artificial Intelligence'."

"List all my bookmark collections."

Troubleshooting LinkAce MCP Server with Pydantic AI

Common issues when connecting LinkAce to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

LinkAce + Pydantic AI FAQ

Common questions about integrating LinkAce MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer — your LinkAce MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.