mcp-management

name

mcp-management

description

Manages MCP (Model Context Protocol) servers for Claude Code and Claude Desktop. Activates for: finding MCP servers, MCP registries, MCP server setup, MCP configuration, MCP troubleshooting, MCP security, building MCP servers, MCP transport selection, claude mcp commands, mcp.json files, mcpServers configuration, tool poisoning prevention, MCP debugging, Smithery, Glama, GitHub MCP registry, which MCP server should I use. NOT for: general Claude Code settings (use claude-code-mastery), OAuth/authentication unrelated to MCP, generic API integrations without MCP.

MCP Management

Comprehensive guide for finding, configuring, securing, and building MCP servers for Claude Code and Claude Desktop.

Quick Navigation

• Find Servers: See Discovering MCP Servers
• Configure Servers: See references/server-configs.md
• Build Custom Servers: See references/building-servers.md
• Security: See references/security-essentials.md
• Troubleshooting: See references/troubleshooting.md
• Enterprise: See references/enterprise-config.md

Platform Differences

Aspect	Claude Code	Claude Desktop
Config location	~/.claude/settings.json	~/Library/Application Support/Claude/claude_desktop_config.json
CLI management	claude mcp add/list/remove	Manual JSON editing
Scopes	local/project/user	Single config
Hot reload	Supported	Requires full restart (Cmd+Q)
Can act as server	Yes (claude mcp serve)	No

Discovering MCP Servers

Primary Registries

Registry	Servers	Best For
Official MCP Registry	Canonical	Verified, authoritative source
GitHub MCP Registry	Curated	GitHub-native, one-click VS Code install
Smithery.ai	4,600+	Usage metrics, edge deployment
Glama.ai	10,000+	Hosted option, no local setup
PulseMCP	7,500+	Daily updates, streaming focus

Specialized Directories

Registry	Focus
Cursor Directory	Cursor IDE optimized (1,800+)
Mastra	Meta-aggregator across registries
MCP.so	Quality-verified listings
Awesome MCP Servers	Community curated GitHub list
HiMCP.ai	Uptime & performance metrics
MCPdb.org	Regional filtering, tech docs
MCPMarket.com	Commercial/enterprise with pricing
Portkey.ai	Enterprise security/compliance
MCPServers.org	User reviews, troubleshooting guides
Cline.bot	Cline AI one-click integration
APITracker.io	API version tracking
AIXploria	Editorial reviews, use-case guides

Evaluation Criteria

When selecting an MCP server:

1. Maintenance: Recent commits? Active issues?
2. Security: Reviewed code? Known vulnerabilities?
3. Token cost: How many tokens does it consume?
4. Transport: HTTP (remote) vs stdio (local)?
5. Trust: Official vs community vs unknown author?

Pre-Installation Workflow

CRITICAL: Before installing ANY MCP server, follow this workflow:

1. Fetch and Read the README

Always retrieve the server's README.md from GitHub or the registry:

# View README directly
gh repo view owner/repo-name

# Or fetch raw README
curl -s https://raw.githubusercontent.com/owner/repo/main/README.md

Look for:

• Required environment variables
• Prerequisites (Node 18+, Python 3.10+, API keys)
• Configuration options and defaults
• Usage examples and limitations
• Security considerations

2. Check for Deprecations

Deprecated	Use Instead
SSE transport	HTTP or stdio (June 2025 spec)
@modelcontextprotocol/server-github	@github/github-mcp-server (April 2025)
OAuth 2.0 for HTTP	OAuth 2.1 required (March 2025 spec)

3. Verify Prerequisites

# Check Node version (18+ typically required)
node --version

# Check Python version (3.10+ for MCP SDK)
python3 --version

# Check if package exists
npm view @package/server-name

4. Review Security Implications

Before proceeding, confirm:

• What filesystem paths can it access?
• What network requests can it make?
• What environment variables does it read?
• Is the source code available and reviewed?

5. Install Following README Instructions

Only after completing steps 1-4, install using the README's recommended method.

Transport Types

Transport	Use When	Example
HTTP	Cloud services, remote APIs	claude mcp add --transport http notion https://mcp.notion.com/mcp
stdio	Local tools, system access	claude mcp add --transport stdio fs -- npx -y @anthropic/mcp-server-filesystem
SSE	Legacy (prefer HTTP)	Deprecated for new implementations

Quick Setup Examples

Claude Code (CLI)

# Add remote server
claude mcp add --transport http github https://api.githubcopilot.com/mcp/

# Add local server
claude mcp add --transport stdio postgres -- npx -y @modelcontextprotocol/server-postgres

# List servers
claude mcp list

# Remove server
claude mcp remove github

Claude Desktop (JSON)

{
  "mcpServers": {
    "github": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-github"],
      "env": {
        "GITHUB_PERSONAL_ACCESS_TOKEN": "ghp_xxx"
      }
    }
  }
}

MCP vs CLI Decision

Use MCP When	Use CLI When
Rich context needed in responses	Simple one-off operations
Complex queries across resources	Quick lookups
Ongoing session work	Infrequent access
Want tool integration	Prefer direct control

Token budget matters: GitHub MCP ~40k tokens. Context7 ~500 tokens. Enable sparingly.

Security Essentials

Critical risks (2025 research: 43% of servers have command injection flaws):

1. Prompt injection: Malicious content in fetched data manipulates Claude
2. Tool poisoning: Malicious tool descriptions trick model into unsafe actions
3. Credential exposure: API keys in version control or logs

Mitigations:

• Only install from trusted registries
• Review server code before installing unknown servers
• Use scoped tokens with minimal permissions
• Never commit credentials to version control
• Enable project-scope servers only after review

See references/security-essentials.md for detailed patterns.

Building MCP Servers

Language Selection

Choose	When
Python	Rapid prototyping, data science tools, existing Python ecosystem
TypeScript	Web integrations, npm ecosystem, type safety preference

Python Quick Start (FastMCP)

from mcp.server.fastmcp import FastMCP

mcp = FastMCP("my-server")

@mcp.tool()
async def my_tool(param: str) -> str:
    """Tool description for Claude."""
    return f"Result: {param}"

if __name__ == "__main__":
    mcp.run(transport="stdio")

TypeScript Quick Start

import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";

const server = new McpServer({ name: "my-server", version: "1.0.0" });

server.registerTool("my_tool", {
  description: "Tool description for Claude",
  inputSchema: { param: z.string() }
}, async ({ param }) => ({
  content: [{ type: "text", text: `Result: ${param}` }]
}));

const transport = new StdioServerTransport();
await server.connect(transport);

Critical: For stdio transport, NEVER write to stdout (corrupts JSON-RPC). Use stderr or logging libraries.

See references/building-servers.md for complete patterns.