AlphaAvatar MCP Plugin
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
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
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:
- Discovers relevant tools
- Validates schemas
- Dispatches calls in parallel
- Aggregates structured responses
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
Installation
pip install alpha-avatar-plugins-mcp
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.
🔐 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
Step 2️⃣ Start AlphaAvatar
Once MCP is enabled and servers are configured:
alphaavatar serve <yarm-file-path>
During startup:
- MCPHost initializes
- All configured MCP servers are connected
- Server metadata is injected into MCP tool description
- MCP becomes available as a unified tool inside the Agent
Metadata
Release files for alpha-avatar-plugins-mcp 0.6.7
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| alpha_avatar_plugins_mcp-0.6.7.tar.gz | 15.0 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| alpha_avatar_plugins_mcp-0.6.7-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 34.6 kB
Release files / alpha_avatar_plugins_mcp-0.6.7.tar.gz
| Download URL | alpha_avatar_plugins_mcp-0.6.7.tar.gz |
|---|---|
| Size | 15.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
|
BLAKE2b-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/7.0.0 CPython/3.11.16
|
Release files / alpha_avatar_plugins_mcp-0.6.7-py3-none-any.whl
| Download URL | alpha_avatar_plugins_mcp-0.6.7-py3-none-any.whl |
|---|---|
| Size | 19.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.11.16
|
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