alpha-avatar-plugins-mcp 0.6.3

AlphaAvatar Framework plugin for MCP service

MCP Plugin for AlphaAvatar

A high-performance Model Context Protocol (MCP) orchestration layer for AlphaAvatar.

This plugin provides a unified, parallel, and latency-optimized interface for discovering and invoking tools exposed by one or more MCP servers — without relying on LiveKit’s native MCP tool injection chain.

We intentionally disable LiveKit’s native “inject each MCP tool into Agent as separate tool” mechanism.

Why?

• Too many tools degrade Agent reasoning performance.
• Serial tool calls increase latency.
• Tool explosion harms LLM decision quality.

Instead, we provide a single unified MCP interface that:

• Supports tool discovery
• Enables parallel execution
• Coordinates multi-server workflows
• Improves overall Agent tool-call performance

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Overview

The MCP Plugin acts as a Tool Orchestrator Middleware between AlphaAvatar Agents and external MCP servers.

It enables:

• 🔍 Tool discovery across heterogeneous MCP servers
• ⚡ Parallel tool execution (concurrent dispatch)
• 🧠 Workflow coordination across multiple servers
• 🔗 Unified abstraction for diverse capabilities (RAG, search, automation, data APIs, etc.)

Unlike traditional tool injection approaches, this design:

• Prevents exponential tool growth inside the Agent
• Reduces reasoning noise
• Avoids serial execution bottlenecks
• Improves scalability for multi-server MCP deployments

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Core Architecture

AlphaAvatar Agent
        │
        ▼
    MCPHost (Unified Tool)
        │
        ├── search_tools()
        └── call_tools()
                │
                ├── MCP Server A
                ├── MCP Server B
                └── MCP Server C

The Agent only sees one tool: MCP.

Internally, MCPHost:

1. Discovers relevant tools
2. Validates schemas
3. Dispatches calls in parallel
4. Aggregates structured responses

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Performance Design Philosophy

❌ What We Avoid

• Injecting hundreds of tools into the Agent
• Serial tool invocation chains
• Tool schema explosion
• Repeated LLM tool selection loops

✅ What We Enable

• Single unified MCP interface
• Parallel tool dispatch
• Multi-server orchestration
• Scalable architecture

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Installation

pip install alpha-avatar-plugins-mcp

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Usage

Step 1️⃣ Enable MCP in Configuration

Enable MCP and register remote MCP servers inside your yaml configuration file.

enable_mcp: true

mcp_servers:
  livekit-docs:
    url: "https://docs.livekit.io/mcp"
    instruction: >
      LiveKit Docs MCP Server provides unified access to the LiveKit ecosystem,
      allowing you to search documentation, explore GitHub code across livekit
      and livekit-examples repositories, retrieve package changelogs, and browse
      Python Agents SDK examples—all in one place.

  github-copilot:
    url: "https://api.githubcopilot.com/mcp/"
    headers:
      Authorization: "Bearer <GITHUB_PAT>"
    instruction: >
      The GitHub MCP server (via GitHub Copilot) enables AI agents to interact
      with repositories, issues, pull requests, and code through a standardized
      MCP interface.

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🔐 Environment Variables

Sensitive credentials such as <GITHUB_PAT> should be injected via environment variables:

export GITHUB_PAT=your_personal_access_token

At runtime:

• The system automatically resolves <GITHUB_PAT>
• Injects it into the request headers
• Keeps secrets out of version-controlled config files

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Step 2️⃣ Start AlphaAvatar

Once MCP is enabled and servers are configured:

alphaavatar serve <yarm-file-path>

During startup:

1. MCPHost initializes
2. All configured MCP servers are connected
3. Server metadata is injected into MCP tool description
4. MCP becomes available as a unified tool inside the Agent