A Rust-based benchmarking tool for measuring MCP (Model Context Protocol) server effectiveness in LLM-assisted development. Compare how different MCP servers impact token usage, cost, and task completion when using Claude Code.
Features
MCP Server Benchmarking: Compare baseline Claude Code performance against MCP-enhanced scenarios
Benchmark tool for measuring MCP server effectiveness in LLM-assisted development
Bintang
1
Tool
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Uptime
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Parallel Execution: Run multiple benchmark containers simultaneously with configurable concurrency
Multi-Runtime Support: Works with Docker and Podman (auto-detection)
Real-time Progress: Live streaming of tool calls and MCP usage during execution
Workspace Isolation: Each run gets a fresh workspace copy to ensure reproducibility
Structured Logging: Tracing-based logging to file and console
Installation
cargo install --path .
Or build from source:
cargo build --release
Requirements
Docker or Podman
Rust 1.75+ (for building)
ANTHROPIC_API_KEY environment variable
Quick Start
1. Initialize Configuration
# Basic configuration
mcp-coder-bench init > mcp-coder-bench.yaml
# With Boarder MCP server example
mcp-coder-bench init --with-boarder > mcp-coder-bench.yaml
2. Validate Configuration
# Check config, workspace, and Docker connectivity
mcp-coder-bench validate
# Also verify container image exists
mcp-coder-bench validate --check-image
3. Run Benchmarks
# Run with default configuration
mcp-coder-bench run
# Run with custom settings
mcp-coder-bench run -p 4 -n 5 # 4 parallel containers, 5 runs each
# Run a single scenario
mcp-coder-bench run --scenario baseline
# Dry-run to validate without executing
mcp-coder-bench run --dry-run
4. Analyze Results
# Terminal table output
mcp-coder-bench analyze results/20260123/
# With statistical analysis
mcp-coder-bench analyze results/20260123/ --stats
# Export as Markdown with charts
mcp-coder-bench analyze results/20260123/ --format markdown --stats -o report.md
# Export as HTML with SVG visualizations
mcp-coder-bench analyze results/20260123/ --format html -o report.html
# Exclude outliers from analysis
mcp-coder-bench analyze results/20260123/ --exclude-outliers
mcp-coder-bench init [OPTIONS]
Options:
-o, --output <FILE> Output file (stdout if not specified)
--with-boarder Include example Boarder MCP configuration
Metrics Collected
Token Usage: Input, output, cache creation, and cache read tokens
Cost: Estimated USD cost based on Claude pricing
Tool Calls: All tools used, with MCP tools tracked separately
Wall Time: Actual execution duration
Success Rate: Task completion status
Statistical Features
Confidence Intervals: 95% CI for token usage and cost (t-distribution for small samples)
Significance Testing: Welch's t-test for comparing scenarios
Effect Sizes: Cohen's d with labels (negligible/small/medium/large)
Outlier Detection: IQR-based outlier identification and filtering
Belum ada daftar tool. Server remote mendapatkannya setelah pemeriksaan kesehatan pertama.
FAQ
Pertanyaan
Bagaimana cara menginstal MCP Coder Bench?
Salin konfigurasi stdio untuk Cursor, Claude Desktop, Claude Code, atau VS Code di halaman ini. Konfigurasi ini memakai instalasi dari penerbit, bukan proxy PlugMCP.
Apakah MCP Coder Bench memerlukan kunci API?
Tidak ada variabel lingkungan wajib yang tercantum di catatan ini.
Transport apa yang digunakan MCP Coder Bench?
MCP Coder Bench berjalan secara lokal melalui stdio.
Kapan MCP Coder Bench terakhir diperiksa?
Terakhir diperiksa 2026-10-28. Benchmark tool for measuring MCP server effectiveness in LLM-assisted development