mcpField
S
Seminara

Seminara

Remote
github.com/shivamselamCommunication1Updated 2w ago
Repository

About Seminara

Seminara is a programmable presentation service for teams and agents, with Aura hosting live, voice-led slide presentations and audience Q&A. Its presentation engine can be orchestrated through SDKs, a CLI, and WebMCP.

Key features

  1. 01Live voice-led presentations
  2. 02Interactive slides and audience Q&A
  3. 03Programmable sessions via SDKs
  4. 04CLI presentation-room creation

Use cases

  1. 01Hosting product demos
  2. 02Running live audience presentations
  3. 03Creating presentation rooms from a terminal

MCP support

Seminara exposes its presentation engine as an MCP server at its core product endpoint and through WebMCP. MCP clients can discover and use its presentation tools.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://seminara.online/api/v1/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

All endpoints
Streamable HTTPhttps://seminara.online/api/v1/mcp
SSEhttps://seminara.online/api/v1/mcp

Tools

Details

From the project README

Seminara Agentic Suite

Now your AI agents can autonomously host live presentations for you.

License: MIT NPM Package PyPI Package Go Reference MCP Compatible Smithery Cursor Directory


View Live Interactive Demo » · Interactive Sandbox » · API Reference » · Seminara Platform »

Seminara Agentic Suite Architecture

The Presentation Layer for AI Agents

Seminara is an autonomous, 24/7 WebRTC presentation host (Aura) that delivers interactive slide decks and fields live audience Q&A.

With the Seminara Agentic Suite, this core engine is now fully programmable. You or your autonomous agents can orchestrate live, voice-led presentations entirely through code using our WebMCP integration, CLI, or multi-language SDKs.


📦 Available Packages & Tools

Package / ToolLanguageDirectoryInstallation
seminara-sdkTypeScript / JavaScriptsdk/npm install seminara-sdk
seminaraPython 3.9+python/pip install seminara
seminara-cliCommand Line CLIcli/npm install -g seminara-cli
goGo 1.21+go/go get github.com/shivamselam/seminara-agentic-suite/go
Go Reference

🚀 Quickstarts: Time to Hello World < 5 Minutes

1. Node.js / TypeScript
npm install seminara-sdk
import { Seminara } from 'seminara-sdk';

const client = new Seminara({ apiKey: process.env.SEMINARA_API_KEY });

// Instantly generate a live, AI-hosted presentation room
const session = await client.sessions.create({
  title: "Q3 Enterprise Demo & Discovery",
  pdfUrl: "https://example.com/pitch-deck.pdf",
  knowledgeBase: [
    { title: "Pricing", content: "Core Host plan is $199/mo for 50 presentations." }
  ],
  ctaText: "Book Architecture Review",
  ctaUrl: "https://seminara.online/book-meeting"
});

console.log(`Live Session URL: ${session.liveLink}`);
2. Python
pip install seminara
import os
from seminara import SeminaraClient

client = SeminaraClient(api_key=os.environ.get("SEMINARA_API_KEY"))

session = client.create_session(
    title="Q3 Enterprise Demo & Discovery",
    is_live=True,
    pdf_url="https://example.com/pitch-deck.pdf",
    knowledge_base=[
        {"title": "Pricing", "content": "Core Host plan is $199/mo for 50 presentations."}
    ],
    cta_text="Book Architecture Review",
    cta_url="https://seminara.online/book-meeting"
)

print(f"Live Session Created: {session['liveLink']}")
3. Command Line (CLI)
npm install -g seminara-cli

# Set your API key
export SEMINARA_API_KEY="sk_live_..."

# Create a presentation room straight from your terminal
seminara create --title "Q3 Product Launch"

# List active rooms
seminara list

🤖 Model Context Protocol (MCP) & AI Connectors

Seminara natively exposes its presentation engine across the entire agent ecosystem:

  • Standard Well-Known Discovery: https://seminara.online/.well-known/mcp
  • Core Product MCP Server: https://seminara.online/api/v1/mcp
  • Documentation MCP Server: https://seminara.online/api/docs/mcp
  • OpenAPI 3.1 Spec (ChatGPT / Custom GPTs): https://seminara.online/openapi.json
  • Discovery Catalog: https://seminara.online/.well-known/api-catalog.json
  • Interactive Sandbox & Zero-Cost Rehearsals: https://seminara.online/sandbox
  • Cursor Directory Plugin: cursor.directory/plugins/seminara-agentic-suite
1-Click Install via Cursor Directory

Install the complete plugin package (Aura subagent, rules, skills, and MCP servers) directly from the Cursor Directory:

Install in Cursor

1-Click Install via Smithery CLI

Installs automatically into Claude Desktop, Cursor, Windsurf, Cline, Zed, and more:

npx -y @smithery/cli install @seminara/autonomous-host

(Or specify client directly: --client claude, --client cursor, --client windsurf, --client cline)

Quick Connect Configurations
Claude Desktop (claude_desktop_config.json)
{
  "mcpServers": {
    "seminara": {
      "type": "sse",
      "url": "https://seminara.online/api/v1/mcp",
      "headers": {
        "Authorization": "Bearer sk_live_your_key_here"
      }
    }
  }
}
Cursor & Windsurf (.cursor/mcp.json or mcp_config.json)
{
  "mcpServers": {
    "seminara": {
      "type": "sse",
      "url": "https://seminara.online/api/v1/mcp"
    }
  }
}
ChatGPT / OpenAI Custom GPTs (Actions)
  1. In your GPT configuration, go to Actions → Create new action.
  2. Click Import from URL and paste: https://seminara.online/openapi.json
  3. Under Authentication, select Bearer and provide your API key.
WebMCP (In-Browser Agents)

If you navigate to https://seminara.online using a WebMCP-enabled browser, your agent will automatically discover the exposed presentation tools on page load.


📖 Documentation & Resources


📄 License

MIT License. Copyright (c) 2026 Shivam Selam / Omni AI Club Private Limited.

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.