Hive (Project Management) MCP Server for LlamaIndex 7 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Hive (Project Management) as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 Hive (Project Management). "
"You have 7 tools available."
),
)
response = await agent.run(
"What tools are available in Hive (Project Management)?"
)
print(response)
asyncio.run(main())
* 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 Hive (Project Management) MCP Server
Connect your Hive account to any AI agent and take full control of your project management and team collaboration through natural conversation.
LlamaIndex agents combine Hive (Project Management) tool responses with indexed documents for comprehensive, grounded answers. Connect 7 tools through the 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
- Workspace Management — List all available workspaces and navigate across different tenant environments effortlessly
- Project Tracking — Analyze grouping schemas linking large initiatives and monitor the status of team projects directly from your agent
- Action Items — Create and list operational tasks (actions), linking precise items and checking team assignments in real-time
- Detailed Inspection — Retrieve exact metadata and structural details for specific action IDs to understand progress and blockers
- Taxonomy & Labels — Discover discrete visual categorizations and taxonomy matrices used to organize your workspace items
- Workflow Templates — Enumerate active repeatable workflows and action templates to maintain process consistency across your team
The Hive (Project Management) MCP Server exposes 7 tools through the Vinkius. Connect it to LlamaIndex 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 Hive (Project Management) to LlamaIndex via MCP
Follow these steps to integrate the Hive (Project Management) MCP Server with LlamaIndex.
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 7 tools from Hive (Project Management)
Why Use LlamaIndex with the Hive (Project Management) MCP Server
LlamaIndex provides unique advantages when paired with Hive (Project Management) through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Hive (Project Management) tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Hive (Project Management) tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Hive (Project Management), a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Hive (Project Management) tools were called, what data was returned, and how it influenced the final answer
Hive (Project Management) + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Hive (Project Management) MCP Server delivers measurable value.
Hybrid search: combine Hive (Project Management) real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Hive (Project Management) 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 Hive (Project Management) for fresh data
Analytical workflows: chain Hive (Project Management) queries with LlamaIndex's data connectors to build multi-source analytical reports
Hive (Project Management) MCP Tools for LlamaIndex (7)
These 7 tools become available when you connect Hive (Project Management) to LlamaIndex via MCP:
create_action
Create action
get_action
Get action
list_actions
List actions
list_labels
List labels
list_projects
List projects
list_templates
List action templates
list_workspaces
List workspaces
Example Prompts for Hive (Project Management) in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Hive (Project Management) immediately.
"List all projects in my 'Marketing' workspace (ID: ws-marketing)"
"Create a new action called 'Finalize Budget' in workspace 'ws-finance'"
"What are the action templates available in the 'Engineering' workspace?"
Troubleshooting Hive (Project Management) MCP Server with LlamaIndex
Common issues when connecting Hive (Project Management) to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpHive (Project Management) + LlamaIndex FAQ
Common questions about integrating Hive (Project Management) MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Hive (Project Management) with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Hive (Project Management) to LlamaIndex
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.