Pumble MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Pumble as an MCP tool provider through 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 Pumble. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Pumble?"
)
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 Pumble MCP Server
Connect your Pumble workspace to any AI agent and bring powerful automation directly to your team's communication hub.
LlamaIndex agents combine Pumble tool responses with indexed documents for comprehensive, grounded answers. Connect 10 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
- Read & Manage Channels — List all public and private channels, fetch detailed metadata, and dynamically create new discussion channels on the fly
- Message Operations — Retrieve conversation histories, post new messages, update typos, or delete outdated announcements seamlessly
- Interactive Reactions — Add emoji reactions to messages automatically to acknowledge requests without cluttering the chat
- User Directory — List all workspace users and pull detailed profiles (including emails and time zones) to ensure accurate tagging
The Pumble MCP Server exposes 10 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 Pumble to LlamaIndex via MCP
Follow these steps to integrate the Pumble 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 10 tools from Pumble
Why Use LlamaIndex with the Pumble MCP Server
LlamaIndex provides unique advantages when paired with Pumble through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Pumble tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Pumble tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Pumble, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Pumble tools were called, what data was returned, and how it influenced the final answer
Pumble + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Pumble MCP Server delivers measurable value.
Hybrid search: combine Pumble real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Pumble 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 Pumble for fresh data
Analytical workflows: chain Pumble queries with LlamaIndex's data connectors to build multi-source analytical reports
Pumble MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Pumble to LlamaIndex via MCP:
chat_add_reaction
Adds an emoji reaction to a message
chat_delete_message
This action is irreversible. Deletes a message from a Pumble channel
chat_history_messages
Retrieves recent messages from a channel
chat_post_message
Specify the channel ID and the message text. Sends a message to a Pumble channel
chat_update_message
Updates a pre-existing message
create_chat_channel
Specify name and whether it should be private. Creates a new communication channel
get_channel_info
Retrieves detailed information about a specific channel
get_user_info
Retrieves detailed information for a specific user
list_all_channels
Lists all public and private channels available in the workspace
list_workspace_users
Lists all users in the Pumble workspace
Example Prompts for Pumble in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Pumble immediately.
"List all our active channels in Pumble."
"Post a message in the #dev-updates channel stating that 'Deployment 2.1 is completed'."
"Read the last 3 messages from #marketing-q4 and react to the last one with a 'thumbsup'."
Troubleshooting Pumble MCP Server with LlamaIndex
Common issues when connecting Pumble to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpPumble + LlamaIndex FAQ
Common questions about integrating Pumble 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 Pumble with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
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 Pumble to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.