Analyze your MCP setup: token costs, grades, duplicates, and optimization tips
Quick Install
Automated & IDE SetupCopy the AI prompt to install this server into Claude Code, Cursor, or another agent โ or use 1-click editor setup below.
Manual Client & Custom JSON ConfigExpand JSON โพ
Client Config & Setup
Choose your client or environment
Target File:
๐ก Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Documentation Overview
mcp-checkup
Your MCP servers are eating your context window. Find out how much.
mcp-checkup is an MCP server that analyzes your MCP setup โ measuring the token cost of every installed server and tool, finding duplicates, grading efficiency, and generating optimization reports.
Quick Start
Then ask your AI assistant:
Why?
Every MCP tool costs 550โ1,400 tokens just for its schema. A server with 50 tools can eat 30,000+ tokens before you type anything. Most developers have no idea how much context window their MCP servers are consuming.
Real examples from the community:
- Adding GitHub MCP increased one user's token usage from 34K to 80K (source)
- One developer found 67,000 tokens consumed by just 4 servers before any conversation (source)
- Context7 (240K weekly downloads) has tool descriptions costing 3x more tokens than necessary (source)
Tools
analyze_servers
Scan your MCP config and measure the token cost of every installed server. Auto-detects config files.
analyze_tools
Deep-dive into a specific server โ per-tool token costs, grades, bloated descriptions, and optimization suggestions.
find_duplicates
Find duplicate tool names across your installed servers. Redundant tools waste context for no benefit.
count_tokens
Count tokens in any text. Useful for estimating context usage.
generate_report
Full markdown health report: server grades (A-F), token costs, duplicates, and actionable recommendations.
Grading System
Per-Tool Grades
| Grade | Tokens | Meaning |
|---|---|---|
| A | โค100 | Excellent โ minimal context cost |
| B | โค300 | Good โ reasonable schema size |
| C | โค600 | Fair โ could be optimized |
| D | โค1000 | Poor โ bloated schema |
| F | >1000 | Failing โ severely impacts context window |
Per-Server Grades
| Grade | Total Tokens | Meaning |
|---|---|---|
| A | โค500 | Lean and efficient |
| B | โค1500 | Reasonable |
| C | โค3000 | Getting heavy |
| D | โค6000 | Significant context cost |
| F | >6000 | Major context window drain |
Installation
Claude Desktop / Claude Code
Cursor
Add to .cursor/mcp.json with the same format.
Auto-Detection
mcp-checkup automatically finds your MCP config in these locations:
.mcp.json(current directory)- Claude Desktop config (Windows/macOS/Linux)
.cursor/mcp.json
Or pass a custom path to any tool.
How It Compares
| Tool | Purpose | Approach |
|---|---|---|
| mcp-checkup | Diagnose token costs | Analyze & report โ see exactly what each tool costs |
| lean-ctx | Reduce token usage | Compress context at runtime |
| MCP Inspector | Debug MCP servers | Test connections and tool calls |
Use mcp-checkup first to find the problem, then decide how to fix it.
Part of the MCP Toolkit
- webcheck-mcp โ Website health analysis
- git-summary-mcp โ Git repository intelligence
- mcp-checkup โ MCP setup health analyzer
- dev-utils-mcp โ Developer utilities
- codescan-mcp โ Codebase health scanner
- deadlink-checker-mcp โ Dead link detector
License
MIT
Related MCP Servers
Reviews
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Frequently Asked Questions about MCP Checkup
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<a href="https://allmcps.com/mcp/mcp-checkup"><img src="https://allmcps.com/api/badge/mcp-checkup?style=directory" alt="MCP Checkup on AllMCPs" /></a>Technical Specs & Signals
CategoryFinance & Fintech
27Quality signal: Emerging ยท 27/100How this signal is calculated โพ
Server availabilityNot measured
Not scored for repo-hosted servers โ we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.
Verified ownership8/20
Documentation & tools11/30
Adoption & activity1/15
Community engagement0/10
A guidance signal from public completeness & health data โ not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.
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