MCP Orchestrator
Aggregates tools from multiple MCP servers with unified BM25/regex search and deferred loading
MCP Orchestrator
A central hub that connects to multiple downstream MCP servers, aggregates their tools, and provides unified access with powerful tool search capabilities.
Built around deferred tool loading — search across all your servers without blowing Claude's context window.
Features
- Config-based Server Registration: Add downstream MCP servers via JSON config file
- Tool Namespacing: Automatic
server_name__tool_nameformat - Tool Search: Unified BM25/regex search with deferred loading support
- Flexible Authentication: Static saved headers or token forwarding
- Multiple Transports: stdio or HTTP
- Tool Definition Caching: Cached definitions, raw result passthrough
- Storage Backends: In-memory (development) or Redis (production)
Quick Start
Installation
pip install mcp-orchestrator
Running the MCP Server
# Run as stdio MCP server (for Claude Desktop, Cursor, etc.)
mcp-orchestrator
# Or run with Python directly
python -m mcp_orchestrator.main
HTTP Transport:
ORCHESTRATOR_TRANSPORT=http ORCHESTRATOR_PORT=8080 python -m mcp_orchestrator.main
This starts the server on http://localhost:8080/mcp with CORS enabled.
Configuring Servers
Add downstream MCP servers in server_config.json:
{
"servers": [
{
"name": "my-server",
"url": "http://localhost:8080/mcp",
"transport": "http",
"auth_type": "static",
"auth_headers": {
"Authorization": "Bearer my-token"
}
},
{
"name": "my-stdio-server",
"url": "server.py",
"transport": "stdio",
"command": "uv",
"args": ["run", "python", "server.py"]
}
]
}
Searching for Tools
The orchestrator provides unified tool search (BM25 by default, regex optional):
# BM25 search (default - natural language)
results = await mcp_client.call_tool("tool_search", {
"query": "get weather information",
"max_results": 3
})
# Regex search (set use_regex=true)
results = await mcp_client.call_tool("tool_search", {
"query": "weather|forecast",
"use_regex": true,
"max_results": 3
})
Architecture
┌─────────────────────────────────────────────────────┐
│ MCP Orchestrator │
│ │
│ ┌──────────────────────────────────────────────┐ │
│ │ FastMCP Server │ │
│ │ ┌─────────────┐ ┌──────────────────┐ │ │
│ │ │ tool_search │ │ call_remote_tool │ │ │
│ │ └─────────────┘ └──────────────────┘ │ │
│ └──────────────────────────────────────────────┘ │
│ │
│ ┌──────────┐ ┌──────────┐ ┌──────────────┐ │
│ │ Server │ │ Tool │ │ Storage │ │
│ │ Registry │ │ Search │ │(Memory/Redis)│ │
│ └──────────┘ └──────────┘ └──────────────┘ │
└─────────────────────────────────────────────────────┘
│
┌───────────────────┼───────────────────┐
▼ ▼ ▼
┌─────────┐ ┌─────────┐ ┌─────────┐
│ MCP Svr │ │ MCP Svr │ │ MCP Svr │
│ #1 │ │ #2 │ │ #N │
└─────────┘ └─────────┘ └─────────┘
Configuration
Environment Variables
| Variable | Default | Description |
|---|---|---|
STORAGE_BACKEND | memory | Storage backend (memory or redis) |
REDIS_URL | redis://localhost:6379/0 | Redis connection URL |
MCP_ORCHESTRATOR_TOOL_CACHE_TTL | 300 | Tool schema cache TTL in seconds |
MCP_ORCHESTRATOR_DEFAULT_CONNECTION_MODE | stateless | Default connection mode |
MCP_ORCHESTRATOR_CONNECTION_TIMEOUT | 30.0 | Connection timeout in seconds |
MCP_ORCHESTRATOR_MAX_RETRIES | 3 | Maximum retry attempts |
ORCHESTRATOR_TRANSPORT | stdio | MCP transport (stdio or http) |
ORCHESTRATOR_PORT | 8080 | Port for HTTP transport |
ORCHESTRATOR_HOST | 0.0.0.0 | Host for HTTP transport |
ORCHESTRATOR_LOG_LEVEL | INFO | Logging level |
SERVER_CONFIG_PATH | server_config.json | Path to server configuration file |
Claude Desktop Integration
Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"mcp-orchestrator": {
"command": "mcp-orchestrator",
"env": {
"STORAGE_BACKEND": "memory",
"ORCHESTRATOR_LOG_LEVEL": "INFO"
}
}
}
}
MCP Tools
tool_search
Search for tools using BM25 relevance ranking or regex pattern matching.
@mcp.tool()
async def tool_search(
query: str,
max_results: int = 3,
use_regex: bool = False,
) -> dict:
"""Search for tools using BM25 or regex.
By default uses BM25 natural language search. Set use_regex=True
to search using Python regex patterns instead.
"""
discover_tools
Discover tools from a registered downstream server.
@mcp.tool()
async def discover_tools(
server_name: str,
) -> dict:
"""Discover tools from a registered server and index them for search.
Returns the list of discovered tools with their schemas.
"""
call_remote_tool
Call a tool directly on a downstream MCP server.
@mcp.tool()
async def call_remote_tool(
tool_name: str,
arguments: Optional[dict] = None,
auth_header: Optional[str] = None,
) -> Any:
"""Call a tool on a downstream server.
Args:
tool_name: Namespaced tool name (server_name__tool_name)
arguments: Tool arguments
auth_header: Optional auth header to override server's configured auth
"""
Tool Search Results
The search tools return results in the format expected by Claude's tool search system:
{
"success": true,
"tool_references": [
{
"type": "tool_reference",
"tool_name": "server_name__tool_name"
}
],
"total_matches": 5,
"query": "weather"
}
Testing
Run the test suite:
uv run pytest
Run with coverage:
uv run pytest --cov=mcp_orchestrator
Project Structure
mcp-orchestrator/
├── src/mcp_orchestrator/
│ ├── __init__.py
│ ├── main.py # Entry point
│ ├── models.py # Pydantic models
│ ├── mcp_server.py # FastMCP server
│ ├── config_loader.py # Config file loader
│ ├── server/
│ │ └── registry.py # Server registry
│ ├── tools/
│ │ ├── router.py # Tool router
│ │ └── search.py # Tool search service
│ └── storage/
│ ├── base.py # Storage interface
│ ├── memory.py # In-memory backend
│ └── redis.py # Redis backend
├── tests/
│ ├── test_registry.py
│ ├── test_search.py
│ ├── test_storage.py
│ ├── test_models.py
│ └── test_integration.py
├── server_config.json # Pre-configured downstream servers
├── pyproject.toml
├── README.md
└── .env # Environment variables (not committed)
License
MIT License
Contributing
Contributions are welcome! Please see CONTRIBUTING.md for guidelines.
Похожие серверы
Scout Monitoring MCP
спонсорPut performance and error data directly in the hands of your AI assistant.
Alpha Vantage MCP Server
спонсорAccess financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
FAL Imagen 4
Generate high-quality images using Google's Imagen 4 Ultra model via the FAL AI platform.
MCP Memory Keeper
A server for persistent context management in Claude AI coding assistants, using a local SQLite database for storage.
Ollama MCP Bridge
A bridge API service connecting Ollama with Model Context Protocol (MCP) servers.
Tencent Cloud Code Analysis
An official MCP server for Tencent Cloud Code Analysis (TCA) to quickly start code analysis and obtain reports.
Kaggle MCP
Get access to Kaggle's datasets, models, competitions, notebook and benchmarks.
CodeSeeker
Graph-powered code intelligence MCP server with semantic search, knowledge graph, and dependency analysis for Claude Code, Cursor, and Copilot.
Contrast MCP Server
Remediate vulnerabilities found by Contrast products using LLM and Coding Agent capabilities.
Unity Code MCP Server
Powerful tool for the Unity Editor that gives AI Agents ability to perform any action using Unity Editor API, like modification of scripts, scenes, prefabs, assets, configuration and more.
Muster
A universal control plane for managing MCP servers and providing intelligent tool discovery for AI agents.
WordPress Feel Chatbot Plugin
A WordPress plugin that transforms a WordPress site into an MCP server, allowing direct access to its content.