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 CrewAI 9 tools — connect in under 2 minutes

Name: LinkAce
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 9 Tools Framework

Connect your CrewAI agents to LinkAce through the Vinkius — pass the Edge URL in the `mcps` parameter and every LinkAce tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="LinkAce Specialist",
    goal="Help users interact with LinkAce effectively",
    backstory=(
        "You are an expert at leveraging LinkAce tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token — get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in LinkAce "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 9 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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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.

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

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 CrewAI 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 CrewAI via MCP

Follow these steps to integrate the LinkAce MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py — CrewAI auto-discovers 9 tools from LinkAce

Why Use CrewAI with the LinkAce MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with LinkAce through the Model Context Protocol.

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 the 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

LinkAce + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries LinkAce for raw data, then a second analyst agent cross-references findings and flags anomalies — all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries LinkAce, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain LinkAce tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries LinkAce against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

LinkAce MCP Tools for CrewAI (9)

These 9 tools become available when you connect LinkAce to CrewAI 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 CrewAI

Ready-to-use prompts you can give your CrewAI 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 CrewAI

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

MCP tools not discovered

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

Agent not using tools

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

Timeout errors

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

Rate limiting or 429 errors

The Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

LinkAce + CrewAI FAQ

Common questions about integrating LinkAce MCP Server with CrewAI.

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.

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.

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.

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.

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.