Dashly MCP Server for Pydantic AIGive Pydantic AI instant access to 8 tools to Get Conversation, Get User Details, List Channels, and more
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Dashly through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
Ask AI about this App Connector for Pydantic AI
The Dashly app connector for Pydantic AI 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 pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
agent = Agent(
model="openai:gpt-4o",
mcp_servers=[server],
system_prompt=(
"You are an assistant with access to Dashly "
"(8 tools)."
),
)
result = await agent.run(
"What tools are available in Dashly?"
)
print(result.data)
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.
Pydantic AI validates every Dashly tool response against typed schemas, catching data inconsistencies at build time. Connect 8 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.
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 Pydantic AI 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 Pydantic AI
When Pydantic AI 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 Pydantic AI via MCP
Follow these steps to wire Dashly into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install Pydantic AI
pip install pydantic-aiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use Pydantic AI with the Dashly MCP Server
Pydantic AI provides unique advantages when paired with Dashly through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Dashly integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Dashly connection logic from agent behavior for testable, maintainable code
Dashly + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Dashly MCP Server delivers measurable value.
Type-safe data pipelines: query Dashly with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Dashly tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Dashly and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Dashly responses and write comprehensive agent tests
Example Prompts for Dashly in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI 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 Pydantic AI
Common issues when connecting Dashly to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiDashly + Pydantic AI FAQ
Common questions about integrating Dashly MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.