Dashly MCP Server for LlamaIndexGive LlamaIndex instant access to 8 tools to Get Conversation, Get User Details, List Channels, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Dashly 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 App Connector for LlamaIndex
The Dashly app connector for LlamaIndex is a standout in the Customer Support category — giving your AI agent 8 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 Dashly. "
"You have 8 tools available."
),
)
response = await agent.run(
"What tools are available in Dashly?"
)
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 Dashly MCP Server
Connect your Dashly account to any AI agent and take full control of your conversational marketing and user tracking workflows through natural conversation.
LlamaIndex agents combine Dashly tool responses with indexed documents for comprehensive, grounded answers. Connect 8 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
- User Lifecycle Orchestration — List and manage your entire high-fidelity user database programmatically, retrieving detailed profile metadata and custom property updates
- Conversational Intelligence — Query active chat sessions, retrieve high-fidelity message history, and send instant replies directly through your agent
- Event Tracking Architecture — Programmatically record custom user actions (e.g., 'Pricing Viewed') to maintain a perfectly coordinated audit trail of customer behavior
- Channel Optimization — Access your complete directory of communication channels to coordinate your engagement strategy across multiple touchpoints
- Operational Monitoring — Verify account-level API connectivity and monitor user activity trends directly through your agent for instant performance reporting
The Dashly MCP Server exposes 8 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.
All 8 Dashly tools available for LlamaIndex
When LlamaIndex connects to Dashly through Vinkius, your AI agent gets direct access to every tool listed below — spanning conversational-marketing, user-tracking, lead-nurturing, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Get details for a specific conversation
Get details for a specific user
List communication channels
List recent conversations
List all Dashly users
Send a reply to a conversation
Set custom properties for a user
Track a custom event for a user
Connect Dashly to LlamaIndex via MCP
Follow these steps to wire Dashly into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Dashly MCP Server
LlamaIndex provides unique advantages when paired with Dashly through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Dashly tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Dashly tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Dashly, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Dashly tools were called, what data was returned, and how it influenced the final answer
Dashly + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Dashly MCP Server delivers measurable value.
Hybrid search: combine Dashly real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Dashly 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 Dashly for fresh data
Analytical workflows: chain Dashly queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Dashly in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Dashly immediately.
"List all active chat conversations in my Dashly account."
"Track event 'Newsletter Signup' for user 'user_456'."
"Get the profile metadata for user ID 'user_789'."
Troubleshooting Dashly MCP Server with LlamaIndex
Common issues when connecting Dashly to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpDashly + LlamaIndex FAQ
Common questions about integrating Dashly MCP Server with LlamaIndex.