MCP Connector

Integrate Discord with Your Applications

Name: Integrate Discord with Your Applications
Availability: OnlineOnly
Author: Klavis AI

Discord connector from the Klavis platform's 100+ prebuilt MCP integrations, deployable cloud-hosted, self-hosted via Docker, or through SDK/REST API.

Connect

Works with discord

Klavis AI

Maintainer?

Spark score

out of 100

Updated last month

Version python-v2.20.0

Models

claude

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Why it matters

Connect your applications to Discord to automate communication and manage server interactions. This asset provides an API for sending messages, managing channels, and handling user roles.

Outcomes

What it gets done

Send, edit, and delete messages via API

Manage Discord channels and permissions

Retrieve server and member information

Automate user role assignments

Install

Add it to your toolbox

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/vb-discord | bash

Capabilities

Tools your agent gets

message_management

Send, edit, and delete messages in Discord channels

channel_operations

Manage channels and channel access permissions

server_management

Retrieve server information and member data

user_interactions

Manage user roles and access permissions

bot_operations

Handle Discord-specific bot functions

Overview

Discord MCP Server

This Discord connector is part of Klavis's platform of 100+ prebuilt MCP integrations, provisionable via cloud hosting, Docker self-host, SDK, or REST API. Use it when building an AI agent that needs Discord access and you'd rather use a managed integration platform than build the connector yourself, especially if you also need other Klavis-hosted services.

What it does

This Discord MCP Server is one of the 100+ prebuilt MCP integrations offered by the Klavis platform, which provides OAuth-supported connectors for AI agents alongside Strata (an intelligent connector layer designed to optimize an agent's context window when juggling many tools) and MCP Sandbox (scalable MCP environments for LLM training and reinforcement learning).

When to use - and when NOT to

Use this when you want to add Discord connectivity to an AI agent without building the integration yourself, choosing whichever deployment model fits your setup: fully managed cloud hosting, self-hosted via Docker, or programmatic provisioning through Klavis's SDK or REST API. It fits naturally alongside other Klavis-hosted integrations (Gmail, Slack, GitHub, and more) if you're building an agent that needs to reach several services through one platform rather than wiring up each connector independently.

How to install

Cloud-hosted (fastest): sign up at klavis.ai and follow the quickstart guide.

Self-hosted via Docker (pattern shown for the GitHub integration, applicable per-server):

docker pull ghcr.io/klavis-ai/github-mcp-server:latest
docker run -p 5000:5000 ghcr.io/klavis-ai/github-mcp-server:latest

Via Python SDK:

from klavis import Klavis
from klavis.types import McpServerName

klavis = Klavis(api_key="your-key")
discord = klavis.mcp_server.create_server_instance(
    server_name=McpServerName.DISCORD,
    user_id="user123",
)

Or via REST API:

curl -X POST "https://api.klavis.ai/v1/mcp-server/instance" \
  -H "Authorization: Bearer your-api-key" \
  -H "Content-Type: application/json" \
  -d '{"server_name": "DISCORD", "user_id": "user123"}'

Who it's for

Developers building AI agents that need Discord access, especially those already using or considering the Klavis platform for multiple prebuilt, OAuth-supported integrations rather than maintaining each connector independently.

Source README

🎯 Choose Your Solution

Strata

Intelligent connectors for your AI agent, optimize context window

MCP Integrations

100+ prebuilt integrations out-of-the-box, with OAuth support

MCP Sandbox

scalable MCP environments for LLM training and RL

Quick Start

Option 1: Cloud-hosted - klavis.ai

Quickstart guide →

Option 2: Self-host

# Run any MCP Integration
docker pull ghcr.io/klavis-ai/github-mcp-server:latest
docker run -p 5000:5000 ghcr.io/klavis-ai/github-mcp-server:latest

# Install Open Source Strata locally
pipx install strata-mcp
strata add --type stdio playwright npx @playwright/mcp@latest

Option 3: SDK

# Python SDK
from klavis import Klavis
from klavis.types import McpServerName

klavis = Klavis(api_key="your-key")

# Create Strata instance
strata = klavis_client.mcp_server.create_strata_server(
    user_id="user123",
    servers=[McpServerName.GMAIL, McpServerName.SLACK],
)

# Or use individual MCP servers
gmail = klavis.mcp_server.create_server_instance(
    server_name=McpServerName.GMAIL,
    user_id="user123",
)

// TypeScript SDK
import { KlavisClient, McpServerName } from 'klavis';

const klavis = new KlavisClient({ apiKey: 'your-api-key' });

// Create Strata instance
const strata = await klavis.mcpServer.createStrataServer({
    userId: "user123",
    servers: [Klavis.McpServerName.Gmail, Klavis.McpServerName.Slack],
});

// Or use individual MCP servers
const gmail = await klavis.mcpServer.createServerInstance({
    serverName: McpServerName.GMAIL,
    userId: "user123"
});

Option 4: REST API

# Create Strata server
curl -X POST "https://api.klavis.ai/v1/mcp-server/strata" \
  -H "Authorization: Bearer your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "user_id": "user123",
    "servers": ["GMAIL", "SLACK"]
  }'

# Create individual MCP server
curl -X POST "https://api.klavis.ai/v1/mcp-server/instance" \
  -H "Authorization: Bearer your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "server_name": "GMAIL",
    "user_id": "user123"
  }'

Resources

Made with ❤️ by the Klavis Team

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