How to Use the Infinity Work Manager MCP in LlamaIndex

Q: Can LlamaIndex query Infinity Work Manager boards?

Yes. By calling listboards and indexing the output, your agent gains semantic awareness of your entire workspace structure.

Q: How are item attributes handled in LlamaIndex?

Attributes are retrieved via listattributes and mapped as metadata. This makes filtered searches across custom fields possible.

Index your project data into searchable knowledge bases using LlamaIndex and the Infinity Work Manager MCP Server.

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Connect Infinity Work Manager MCP to LlamaIndex

Create your Vinkius account to connect Infinity Work Manager 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 Infinity Work Manager with LlamaIndex

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Semantic search over Infinity Work Manager

Convert `list_items` and `list_comments` outputs into vector embeddings automatically. LlamaIndex stores this information so your agent can query past project history. Find specific items by describing their content rather than filtering by ID. Your agent identifies the right `get_item` call based on your natural language prompt.

RAG pipelines for project documentation

Ground your AI responses in real-time board data fetched via `get_board`. This prevents hallucinations by forcing the model to reference live attributes. Combine retrieved items with external documents in a unified index. This allows your agent to answer questions about bug resolutions by linking support tickets to Infinity tasks.

Automated tool discovery for LlamaIndex

Use McpToolSpec to convert all 15 tools into executable functions for your agent. The client handles the schema mapping so you can start querying immediately. Filter access by using the allowed_tools parameter to restrict which operations the agent can perform. You maintain control over which boards the model can modify.

Setup guide

Set up Infinity Work Manager 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 Infinity Work Manager 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 Infinity Work Manager tools.",
)
response = await agent.run("List recent Infinity Work Manager data")

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Common questions about Infinity Work Manager MCP in LlamaIndex

Use the BasicMCPClient to connect and then pass the tools to your indexer. The system automatically converts API results into queryable nodes.

Yes. By calling `list_boards` and indexing the output, your agent gains semantic awareness of your entire workspace structure.

Only if you configure your index to save to disk. LlamaIndex keeps the retrieved data in memory during the session by default.

Attributes are retrieved via `list_attributes` and mapped as metadata. This makes filtered searches across custom fields possible.

Your API token is used to fetch data locally. No raw data is sent to third parties, and your vector store remains on your infrastructure.

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