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Texter MCP Server for Pydantic AIGive Pydantic AI instant access to 10 tools to Add Label To Texter Chat, Get Texter Chat Details, List Texter Channels, and more

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Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Texter 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 Texter app connector for Pydantic AI is a standout in the Communication Messaging category — giving your AI agent 10 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python
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 Texter "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Texter?"
    )
    print(result.data)

asyncio.run(main())
Texter
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About Texter MCP Server

Connect your Texter account to any AI agent and simplify how you manage customer conversations across WhatsApp, Instagram, and more through natural conversation.

Pydantic AI validates every Texter tool response against typed schemas, catching data inconsistencies at build time. Connect 10 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

  • Chat Management — List all active chats and retrieve detailed metadata and history for specific conversations.
  • Omichannel Messaging — Send session messages to active chats or use pre-approved templates for new outreach.
  • Conversation Control — Resolve or close chats and apply labels for better organization and tracking.
  • Workspace Oversight — List departments, labels, and connected messaging channels (WhatsApp, Instagram, etc.).
  • Template Automation — Send localized template messages with dynamic components directly via AI.
  • Team Coordination — Monitor active threads and manage chat assignments across your unified inbox.

The Texter MCP Server exposes 10 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 10 Texter tools available for Pydantic AI

When Pydantic AI connects to Texter through Vinkius, your AI agent gets direct access to every tool listed below — spanning sms-marketing, omnichannel, customer-engagement, 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.

add_label_to_texter_chat

Assign a label to a chat

get_texter_chat_details

Get chat details

list_texter_channels

). List connected channels

list_texter_chats

List all active chats

list_texter_departments

List departments

list_texter_labels

List chat labels

list_texter_messages

List messages in a chat

resolve_texter_chat

Resolve or close a chat

send_texter_message

Send a message to an active chat

send_texter_template

Send a WhatsApp/Messenger template message

Connect Texter to Pydantic AI via MCP

Follow these steps to wire Texter into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install Pydantic AI

Run pip install pydantic-ai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save to agent.py and run: python agent.py
04

Explore tools

The agent discovers 10 tools from Texter with type-safe schemas

Why Use Pydantic AI with the Texter MCP Server

Pydantic AI provides unique advantages when paired with Texter through the Model Context Protocol.

01

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

02

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Texter integration code

03

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

04

Dependency injection system cleanly separates your Texter connection logic from agent behavior for testable, maintainable code

Texter + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Texter MCP Server delivers measurable value.

01

Type-safe data pipelines: query Texter with guaranteed response schemas, feeding validated data into downstream processing

02

API orchestration: chain multiple Texter tool calls with Pydantic validation at each step to ensure data integrity end-to-end

03

Production monitoring: build validated alert agents that query Texter and output structured, schema-compliant notifications

04

Testing and QA: use Pydantic AI's dependency injection to mock Texter responses and write comprehensive agent tests

Example Prompts for Texter in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Texter immediately.

01

"List all active chats in my Texter account."

02

"Send the 'order_confirmed' template in 'pt_BR' to 5511999999999."

03

"Mark chat 'chat_10293' as resolved and add the label 'Support-Fixed'."

Troubleshooting Texter MCP Server with Pydantic AI

Common issues when connecting Texter to Pydantic AI through the Vinkius, and how to resolve them.

01

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Texter + Pydantic AI FAQ

Common questions about integrating Texter MCP Server with Pydantic AI.

01

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.
02

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.
03

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Texter MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.