mcp-server-orchestrator
Configure, deploy, and troubleshoot Model Context Protocol (MCP) servers for AI agent workflows. Use when setting up MCP servers, debugging connection issues, managing multi-server configurations, integrating with Claude Desktop/Code/Cowork, or designing custom tool servers. Triggers on MCP configuration, tool server development, Claude integration issues, or agent infrastructure setup.
Best use case
mcp-server-orchestrator is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Configure, deploy, and troubleshoot Model Context Protocol (MCP) servers for AI agent workflows. Use when setting up MCP servers, debugging connection issues, managing multi-server configurations, integrating with Claude Desktop/Code/Cowork, or designing custom tool servers. Triggers on MCP configuration, tool server development, Claude integration issues, or agent infrastructure setup.
Teams using mcp-server-orchestrator should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/mcp-server-orchestrator/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How mcp-server-orchestrator Compares
| Feature / Agent | mcp-server-orchestrator | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Configure, deploy, and troubleshoot Model Context Protocol (MCP) servers for AI agent workflows. Use when setting up MCP servers, debugging connection issues, managing multi-server configurations, integrating with Claude Desktop/Code/Cowork, or designing custom tool servers. Triggers on MCP configuration, tool server development, Claude integration issues, or agent infrastructure setup.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# MCP Server Orchestrator
Manage MCP server infrastructure for AI-powered development workflows.
## MCP Architecture Overview
```
┌─────────────────┐ ┌──────────────────┐ ┌─────────────────┐
│ MCP Client │────▶│ MCP Server │────▶│ External APIs │
│ (Claude, etc.) │◀────│ (Tool Provider) │◀────│ (Services) │
└─────────────────┘ └──────────────────┘ └─────────────────┘
│ │
└───── JSON-RPC ────────┘
```
**Key concepts:**
- **Server**: Provides tools, resources, and prompts via MCP protocol
- **Client**: Consumes server capabilities (Claude Desktop, Claude Code, etc.)
- **Transport**: Communication layer (stdio, SSE, WebSocket)
## Configuration Locations
| Client | Config File | Platform |
|--------|------------|----------|
| Claude Desktop | `claude_desktop_config.json` | macOS: `~/Library/Application Support/Claude/` |
| | | Windows: `%APPDATA%\Claude\` |
| Claude Code | `settings.json` or MCP config | Project-level or user settings |
| Cline | `cline_mcp_settings.json` | VS Code extension settings |
## Server Configuration Schema
```json
{
"mcpServers": {
"server-name": {
"command": "executable",
"args": ["arg1", "arg2"],
"env": {
"API_KEY": "value"
},
"disabled": false
}
}
}
```
### Common Server Types
**Python Server (uvx)**:
```json
{
"my-python-server": {
"command": "uvx",
"args": ["--from", "package-name", "server-command"]
}
}
```
**Node Server (npx)**:
```json
{
"my-node-server": {
"command": "npx",
"args": ["-y", "@scope/package-name"]
}
}
```
**Local Development Server**:
```json
{
"dev-server": {
"command": "python",
"args": ["-m", "my_server"],
"env": {
"DEBUG": "true"
}
}
}
```
## Troubleshooting Workflow
### Connection Issues
1. **Verify server starts independently**:
```bash
# Test Python server
python -m my_server
# Test Node server
npx -y @scope/package-name
```
2. **Check logs**:
- Claude Desktop: `~/Library/Logs/Claude/mcp*.log`
- Look for JSON-RPC errors, connection timeouts
3. **Validate JSON config**:
```bash
python -c "import json; json.load(open('config.json'))"
```
4. **Common fixes**:
- Use absolute paths for commands
- Ensure dependencies installed in correct environment
- Check API keys/env vars are set
- Restart client after config changes
### Authentication Issues
1. **OAuth flows**: Ensure redirect URIs configured correctly
2. **API keys**: Verify env vars accessible to server process
3. **Token refresh**: Check token storage location and permissions
## Building Custom Servers
### Python Server (FastMCP)
```python
from fastmcp import FastMCP
mcp = FastMCP("my-server")
@mcp.tool()
def my_tool(param: str) -> str:
"""Tool description for the AI."""
return f"Result: {param}"
@mcp.resource("resource://my-data")
def get_data() -> str:
"""Provide data as a resource."""
return "Resource content"
if __name__ == "__main__":
mcp.run()
```
### Node Server (MCP SDK)
```typescript
import { Server } from "@modelcontextprotocol/sdk/server/index.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
const server = new Server({ name: "my-server", version: "1.0.0" }, {
capabilities: { tools: {} }
});
server.setRequestHandler(ListToolsRequestSchema, async () => ({
tools: [{
name: "my_tool",
description: "Tool description",
inputSchema: { type: "object", properties: { param: { type: "string" } } }
}]
}));
const transport = new StdioServerTransport();
await server.connect(transport);
```
## Multi-Server Orchestration
### Modular Architecture
Organize servers by domain:
```json
{
"mcpServers": {
"filesystem": { "command": "...", "args": ["--allowed-dirs", "/projects"] },
"database": { "command": "...", "env": { "DB_URL": "..." } },
"api-integrations": { "command": "...", "env": { "API_KEYS": "..." } },
"custom-tools": { "command": "python", "args": ["-m", "my_tools"] }
}
}
```
### Server Selection Strategy
Think of servers as modules in a synthesizer—patch them together based on workflow needs:
- **Development workflow**: filesystem + git + code-analysis servers
- **Research workflow**: web-search + document + note-taking servers
- **Data workflow**: database + visualization + export servers
## Performance Optimization
- **Lazy loading**: Only enable servers needed for current task
- **Caching**: Implement response caching for expensive operations
- **Timeout tuning**: Adjust timeouts for slow external APIs
- **Connection pooling**: Reuse connections in database servers
## References
- `references/server-templates.md` - Boilerplate for common server types
- `references/debugging-guide.md` - Detailed troubleshooting proceduresRelated Skills
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