zipBoard MCP Server for LlamaIndexGive LlamaIndex instant access to 6 tools to Create Project, Create Task, Get Organization, and more

Name: zipBoard
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add zipBoard as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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The zipBoard MCP Server for LlamaIndex is a standout in the Industry Titans category — giving your AI agent 6 tools to work with, ready to go from day one.

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python

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

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to zipBoard. "
            "You have 6 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in zipBoard?"
    )
    print(response)

asyncio.run(main())

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About zipBoard MCP Server

Connect your zipBoard account to any AI agent to streamline your visual review and bug tracking workflows. zipBoard provides a powerful platform for collecting feedback on websites, images, and PDF documents through natural conversation.

LlamaIndex agents combine zipBoard tool responses with indexed documents for comprehensive, grounded answers. Connect 6 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

What you can do

Project Orchestration — List all your visual review projects and retrieve detailed metadata including owners and configurations.
File & URL Management — Access and monitor the files, URLs, and documents being reviewed within your projects.
Task & Issue Tracking — List and create tasks/bugs with direct control over priorities and assignees to ensure efficient QA.
Organization Insights — Retrieve detailed information about your zipBoard organization to maintain an overview of your team's structure.
Real-time Feedback — Get a comprehensive overview of active issues and feedback cycles using natural language commands.

The zipBoard MCP Server exposes 6 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 6 zipBoard tools available for LlamaIndex

When LlamaIndex connects to zipBoard through Vinkius, your AI agent gets direct access to every tool listed below — spanning bug-tracking, visual-feedback, issue-management, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

create

Create project on zipBoard

Pass data as a JSON string. Create a new project

create

Create task on zipBoard

Create a new task/issue

get

Get organization on zipBoard

Get organization details

list

List files on zipBoard

List project files/URLs

list

List projects on zipBoard

List all zipBoard projects

list

List tasks on zipBoard

List project tasks/issues

Connect zipBoard to LlamaIndex via MCP

Follow these steps to wire zipBoard into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

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 6 tools from zipBoard

Why Use LlamaIndex with the zipBoard MCP Server

LlamaIndex provides unique advantages when paired with zipBoard through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine zipBoard tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain zipBoard tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query zipBoard, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what zipBoard tools were called, what data was returned, and how it influenced the final answer

zipBoard + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the zipBoard MCP Server delivers measurable value.

Hybrid search: combine zipBoard real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query zipBoard to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying zipBoard for fresh data

Analytical workflows: chain zipBoard queries with LlamaIndex's data connectors to build multi-source analytical reports

Example Prompts for zipBoard in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with zipBoard immediately.

"List all active review projects in zipBoard."

"Show me the pending bugs for the 'Mobile App QA' project."

Troubleshooting zipBoard MCP Server with LlamaIndex

Common issues when connecting zipBoard to LlamaIndex through Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

zipBoard + LlamaIndex FAQ

Common questions about integrating zipBoard MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query zipBoard tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.