How to Use the Ayanza MCP in LlamaIndex

Q: How do I index Ayanza wiki pages into LlamaIndex?

You use the MCP tool spec to fetch data using listwikipages. The tool output is converted into document nodes that LlamaIndex embeds into your vector store.

Q: Can my LlamaIndex agent write new tasks back to Ayanza?

Yes, your agent can call createtask or updatetask based on search results. It uses the tool list generated by the MCP client to execute these actions.

Q: How does LlamaIndex protect my Ayanza wiki and task content?

All data fetched from listwikipages or getproject runs inside a zero-trust, isolated V8 environment. Your workspace data is never used for training and is cleared as soon as the session ends.

Index your Ayanza wiki pages and tasks directly into LlamaIndex to build search agents grounded in live team data.

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Connect Ayanza MCP to LlamaIndex

Create your Vinkius account to connect Ayanza 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 Ayanza with LlamaIndex

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Semantic Search Over Ayanza Wikis

The LlamaIndex integration uses `list_wiki_pages` to pull your team's internal documentation directly into your vector index. Your agent queries this index to answer complex questions using actual workspace data instead of guessing. Every document retrieved from Ayanza is parsed and embedded dynamically. This gives your query engine a live feed of company knowledge that stays accurate as your team updates pages.

Grounding LLM Responses with the Ayanza MCP Server

This toolset provides `list_tasks` and `get_project` to ground your RAG applications in real-time project metrics. The agent queries your workspace tasks, embeds the results, and matches them against user questions. You avoid outdated context because LlamaIndex pulls fresh records on demand. The agent combines live task statuses with your historical documents to build a unified, queryable knowledge base.

Automated Task Context Injection

Your agent runs `get_task` to pull detailed descriptions and metadata before generating project summaries. LlamaIndex indexes these task details so your agent can cross-reference them with team members retrieved via `list_users`. This setup turns raw API outputs into structured index nodes. Your agent gets the full picture of who is working on what without manual data entry.

Setup guide

Set up Ayanza 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 Ayanza 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 Ayanza tools.",
)
response = await agent.run("List recent Ayanza 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 Ayanza. 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 Ayanza MCP in LlamaIndex

You use the MCP tool spec to fetch data using `list_wiki_pages`. The tool output is converted into document nodes that LlamaIndex embeds into your vector store.

Yes, your agent can call `create_task` or `update_task` based on search results. It uses the tool list generated by the MCP client to execute these actions.

Vinkius hosts the server in a sandbox that manages API traffic smoothly. Your LlamaIndex agent can run multiple queries to `list_tasks` without hitting connection blocks.

Yes, you can use LlamaIndex's allowed tools filter to restrict access. For example, you can expose `list_projects` while blocking `delete_task` for safety.

All data fetched from `list_wiki_pages` or `get_project` runs inside a zero-trust, isolated V8 environment. Your workspace data is never used for training and is cleared as soon as the session ends.

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