mcp-optimizer
Use when optimizing MCP server usage to reduce token overhead. Helps select appropriate servers based on task type.
$ Installieren
git clone https://github.com/duc01226/EasyPlatform /tmp/EasyPlatform && cp -r /tmp/EasyPlatform/.github/skills/mcp-optimizer ~/.claude/skills/EasyPlatform// tip: Run this command in your terminal to install the skill
name: mcp-optimizer description: Use when optimizing MCP server usage to reduce token overhead. Helps select appropriate servers based on task type.
MCP Optimizer Skill
Purpose
Optimize MCP server usage to reduce token overhead. Each MCP server consumes tokens for tool definitions - this skill helps select only the servers needed for the current task.
Token Impact Reference
| Server | Approximate Tokens | Use Cases |
|---|---|---|
| playwright | ~5K | UI testing, screenshots, browser automation |
| memory | ~2K | Context persistence, session continuity |
| sequential-thinking | ~1K | Complex reasoning, multi-step problems |
| github | ~3K | PR management, issue tracking |
| filesystem | ~2K | Enhanced file operations |
| Total | ~13K | All servers loaded |
Task-Based Server Recommendations
Backend Development
Recommended servers: memory, sequential-thinking Token savings: ~8K (60%)
Tasks: CQRS commands, entity development, data migrations
Frontend Development
Recommended servers: memory, playwright, sequential-thinking Token savings: ~5K (38%)
Tasks: Component development, UI testing, form validation
PR/Issue Workflow
Recommended servers: memory, github Token savings: ~8K (60%)
Tasks: Create PRs, fix issues, code review
Debugging
Recommended servers: memory, sequential-thinking, playwright Token savings: ~5K (38%)
Tasks: Bug diagnosis, root cause analysis, behavior verification
Code Review
Recommended servers: memory, github Token savings: ~8K (60%)
Tasks: Review changes, check patterns, verify compliance
Architecture/Planning
Recommended servers: memory, sequential-thinking Token savings: ~8K (60%)
Tasks: Design decisions, impact analysis, dependency mapping
Optimization Strategies
1. Session Cleanup
Use /clear command after completing major tasks to reset context:
/clear
This removes accumulated tool outputs and conversation history while preserving essential context.
2. MAX_MCP_OUTPUT_TOKENS
Set environment variable to limit MCP tool output size:
export MAX_MCP_OUTPUT_TOKENS=25000
This prevents large tool outputs from consuming excessive context.
3. Selective Tool Usage
When a task doesn't need specific MCP capabilities:
- Skip Playwright for backend-only work
- Skip GitHub when not doing PR/issue work
- Keep Memory for session continuity (always recommended)
- Keep Sequential-Thinking for complex reasoning
4. Deferred Tool Discovery
For large result sets, use filtering before full retrieval:
# Instead of getting all, filter first
mcp__memory__search_nodes({ query: "specific-term" })
# Then open only relevant nodes
mcp__memory__open_nodes({ names: ["specific-entity"] })
Server Configuration Guide
The MCP server configuration is in .mcp.json:
{
"mcpServers": {
"server-name": {
"command": "cmd",
"args": ["/c", "npx", "-y", "@package/name"],
"description": "Purpose description"
}
}
}
To Temporarily Disable a Server
Comment out or remove from .mcp.json, then restart Claude Code.
Task-Specific Configurations
Consider creating task-specific MCP configurations:
.mcp.json # Full configuration (default)
.mcp.backend.json # Backend-focused (memory, sequential-thinking)
.mcp.frontend.json # Frontend-focused (memory, playwright)
.mcp.pr-workflow.json # PR workflow (memory, github)
Token Budget Planning
For 200K context window:
| Usage | Tokens | Percentage |
|---|---|---|
| MCP Tools (all) | ~13K | 6.5% |
| CLAUDE.md | ~15K | 7.5% |
| Skills (loaded) | ~5K | 2.5% |
| Instructions | ~3K | 1.5% |
| Available for work | ~164K | 82% |
With optimization (backend-only):
| Usage | Tokens | Percentage |
|---|---|---|
| MCP Tools (optimized) | ~3K | 1.5% |
| CLAUDE.md | ~15K | 7.5% |
| Skills (loaded) | ~5K | 2.5% |
| Instructions | ~3K | 1.5% |
| Available for work | ~174K | 87% |
Net gain: 10K tokens (5% improvement)
Best Practices
- Start minimal - Enable only needed servers at session start
- Add as needed - Enable additional servers when task requires
- Clear regularly - Use
/clearafter major task completion - Monitor usage - Watch token indicator during complex sessions
- Store context - Use Memory MCP before clearing to preserve learnings
Verification Checklist
Before starting a session, consider:
[ ] What type of task am I doing?
[ ] Which MCP servers are needed?
[ ] Can I disable unused servers?
[ ] Should I clear previous context?
[ ] Is Memory MCP preserving important context?
Repository
