How do I get my CometChat API credentials?

Log in to the CometChat dashboard at app.cometchat.com. Your App ID, Region, and API Key are displayed on the app overview page.

What is the difference between UID and GUID?

UID (User ID) is the unique identifier for a user. GUID (Group ID) is the unique identifier for a group. Both are used to target specific resources in the API.

Can I send files with this integration?

The current version supports text messages. File and media sending may be added in future updates.

CometChat MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: CometChat
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect CometChat through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

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 CometChat "
            "(10 tools)."
        ),
    )

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

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 CometChat MCP Server

Connect your AI assistant to CometChat, the communication platform providing chat, voice, and video capabilities for applications.

Pydantic AI validates every CometChat 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

User Management — List registered users, check online status, and retrieve user profiles.
Group Operations — Create, list, and manage chat groups with different privacy settings.
Message History — Retrieve conversation histories for users or groups and search past messages.

The CometChat 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.

How to Connect CometChat to Pydantic AI via MCP

Follow these steps to integrate the CometChat MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

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 CometChat with type-safe schemas

Why Use Pydantic AI with the CometChat MCP Server

Pydantic AI provides unique advantages when paired with CometChat 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 CometChat integration code

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

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

CometChat + Pydantic AI Use Cases

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

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

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

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

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

CometChat MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect CometChat to Pydantic AI via MCP:

create_group

Create a new group in CometChat

create_user

Create a new user in CometChat

deactivate_user

Deactivate a user instead of deleting them

delete_user

Permanently delete a user from CometChat

get_group_details

Retrieve details of a specific group

get_user

Retrieve detailed information about a specific user

list_groups

Retrieve a list of groups from CometChat

list_messages

Retrieve chat history messages

list_users

Retrieve a list of users from CometChat

send_message

Send a text message to a user or group

Example Prompts for CometChat in Pydantic AI

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

"Show me the first 20 users in CometChat."

"Create a public group named 'Marketing Team' with GUID 'marketing-team'."

"Retrieve the conversation history between users 'alice' and 'bob'."

Troubleshooting CometChat MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

CometChat + Pydantic AI FAQ

Common questions about integrating CometChat MCP Server with Pydantic AI.

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.

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.

Can I switch LLM providers without changing MCP code?

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