This Claude skill provides universal patterns and best practices for integrating Multi-Client Protocol (MCP) servers into agentic workflows. It streamlines server discovery, selection, and implementation across various domains—such as memory management, issue tracking, and web content ingestion—ensuring robust, scalable, and predictable AI agent operations.

When should I use mcp-servers?

mcp-servers is useful in the following scenarios: • Standardizing tool integration across multiple AI agent projects using a unified protocol to reduce development overhead. • Implementing efficient server discovery and health checks to ensure agent reliability and prevent runtime failures. • Orchestrating complex workflows that require multiple specialized MCP servers, such as combining semantic code search with long-term memory recall. • Managing project-specific context and error handling when agents interact with external data sources like GitHub, Upstash, or local file systems.

name	mcp-servers
description	Universal patterns for using MCP (Multi-Client Protocol) servers in agentic workflows
license	MIT
compatibility	opencode
related_issue_tracking	For task management with MCP servers, use skill `issue-tracking`
related_knowledge_management	For memory and knowledge storage, use skill `knowledge-management`

MCP Servers

What I Do

Provide universal patterns and best practices for integrating MCP servers into agentic workflows across different projects and domains.

Universal MCP Server Patterns

Server Discovery and Selection

Keep the authoritative list of servers in .vscode/mcp.json and audit it whenever project needs change
Document server capabilities (inputs, outputs, limitations) so agents can choose correctly without probing
Verify availability early by issuing lightweight health or list_* commands rather than waiting for first real use
Prefer a small, purposeful tool set to keep the assistant's tool offers focused and predictable

Common MCP Server Types

Server Type	Typical Use Cases	Integration Pattern
`memorygraph`	Long-term knowledge storage	`recall_memories(query="project-specific knowledge")`
`beads-mcp`	Issue tracking	`bd ready --json`
`sequential-thinking`	Complex problem analysis	Multi-step thought process
`desktop-commander`	File operations	Unified file system interface
`serena`	Semantic code operations	Symbol-level code retrieval and editing
`fetch`	Web content ingestion	`fetch(url="https://example.com")`
`gh_grep`	Public GitHub code search	Query literal or regex patterns across repos
`upstash-context7`	Documentation recall	Natural language queries over curated doc sets

Simple Utility Servers

These lightweight servers complement the core development stack without overwhelming the assistant:

fetch — Retrieves up-to-date web content (HTML, markdown, raw text). Use it for vendor docs or standards that change frequently.
gh_grep — Mirrors grep.app functionality for discovering real-world code snippets. Use literal or regex queries to find idiomatic usage.
upstash-context7 — Provides semantic retrieval across curated documentation (e.g., vendor APIs, SDK guides). Query with natural language to ground decisions in official sources.

Integration Best Practices

Context Management: Always load project context before using MCP servers
Error Handling: Implement graceful fallbacks when servers are unavailable
Performance: Cache frequently used server responses
Security: Validate server responses before processing

When to Use Me

Use this skill when:

Setting up MCP server integrations in new projects
Standardizing agent tool usage across multiple projects
Creating reusable agent workflows
Implementing cross-project knowledge sharing

Universal Examples

Memory Graph Integration

# Universal memory storage pattern
store_memory(
    type="solution",
    title="Cross-project solution pattern",
    content="Reusable approach for X",
    tags=["universal", "pattern"],
    importance=0.8
)

# Universal memory recall
memories = recall_memories(
    query="reusable patterns",
    memory_types=["solution", "pattern"]
)

Issue Tracking Workflow

# Universal issue creation
issue = bd_create(
    title="Implement universal pattern",
    description="Create reusable component for X",
    issue_type="feature",
    priority=1
)

# Universal issue management
bd_update(issue.id, status="in_progress")

Compatibility Notes

This skill is designed to work with:

OpenCode agent framework
Claude-compatible MCP clients
Any project using MCP servers
Cross-project knowledge sharing workflows

When & Why to Use This Skill

Use Cases