How to Use the LinkAce MCP in LlamaIndex

Q: Can LlamaIndex query specific LinkAce collections?

Yes, the agent can call listallcollections to find the correct folder ID. It then uses that ID to filter bookmarks before generating answers.

Q: Does LlamaIndex support live search in LinkAce?

Yes, the searchbookmarks tool allows the agent to query your live LinkAce instance in real time. This ensures your RAG pipeline always has access to the latest links you have saved through this MCP Server.

Q: Can I write new bookmarks back to LinkAce from my agent?

You can use createnewbookmark and createnewtag within your agent workflows. This allows your system to archive useful sources it discovers during web research tasks using these MCP tools.

Turn your LinkAce web archive into a searchable knowledge index for your LlamaIndex RAG pipelines.

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Connect LinkAce MCP to LlamaIndex

Create your Vinkius account to connect LinkAce to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup LinkAce with LlamaIndex

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Index LinkAce bookmarks using LlamaIndex

This MCP Server connects your bookmark database directly to your vector store using the `list_all_bookmarks` tool. Instead of basic keyword matching, your LlamaIndex application performs semantic searches over your entire saved web history. The `get_bookmark_details` tool pulls down the full metadata for any saved link. This allows your indexer to build rich document nodes that contain tags, descriptions, and creation dates for highly accurate retrieval.

Keep your RAG knowledge base fresh

The `list_all_tags` tool lets your indexing pipeline track how your library changes over time. Your agent can scan for new tags and selectively ingest only the bookmarks that match specific categories. When you add a new link using `create_new_bookmark`, your LlamaIndex agent can automatically trigger a document update. This keeps your local vector index in sync with your live LinkAce database without manual re-indexing.

Query live bookmark data with agentic RAG

The `search_bookmarks` tool gives your query engine direct access to your live LinkAce account. When a user asks a question, the agent searches your bookmarks first to ground its answers in sources you have personally vetted. By using `list_all_collections`, your agent can restrict its search to specific folders or topics. This prevents irrelevant bookmarks from cluttering the context window and wasting LLM tokens.

Setup guide

Set up LinkAce MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all LinkAce MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to LinkAce tools.",
)
response = await agent.run("List recent LinkAce data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by LinkAce. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about LinkAce MCP in LlamaIndex

Use the llama-index-tools-mcp package to initialize the basic MCP client. From there, convert the server tools to a list using the tool spec and pass them to your agent.

Yes, the agent can call `list_all_collections` to find the correct folder ID. It then uses that ID to filter bookmarks before generating answers.

Yes, the `search_bookmarks` tool allows the agent to query your live LinkAce instance in real time. This ensures your RAG pipeline always has access to the latest links you have saved through this MCP Server.

You can use `create_new_bookmark` and `create_new_tag` within your agent workflows. This allows your system to archive useful sources it discovers during web research tasks using these MCP tools.

All data transfers containing your saved URLs and personal tags remain inside your private Vinkius MCP isolate. No external servers store your API credentials, keeping your personal web archive completely private.

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