EvalKit MCP Server

EvalKit MCP Server

Enables testing AI safety classifier robustness against query decomposition, obfuscation, and multi-agent attacks. Provides tools for full evaluation pipelines, query previews, and status checks.

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README

EvalKit — Classifier Robustness Evaluation Toolkit

Python 3.11+ License Anthropic

Multi-technique evaluation toolkit for testing AI safety classifier robustness against query decomposition, obfuscation, and multi-agent orchestration attacks. MCP plugin for Claude Code.

Quick Start

uv sync                          # install everything
claude                           # MCP tools auto-loaded from .mcp.json

Architecture

User Query → SPLITTER → [Encoder → Wrapper → ApiClient] × N → MERGER → Report

Usage

In Claude Code (MCP)

Tool Purpose
eval_classifier_robustness Full eval pipeline
eval_decompose_query Preview query decomposition
eval_obfuscation_evasion Test homoglyph substitution
eval_status Check configuration

Via CLI

python3 run.py decompose "query" 5        # decompose into sub-queries
python3 run.py eval "query"               # full evaluation pipeline
python3 run.py obfuscate "text"           # test obfuscation

Benchmark

python3 benchmark.py                     # dry run (no API key)
python3 benchmark.py --quick             # single query smoke test
python3 benchmark.py --json report.json  # save JSON results
python3 benchmark.py --html report.html  # save HTML report
ANTHROPIC_API_KEY=sk-... python3 benchmark.py  # live test

Configuration

Parameter Values Default Description
obfuscation none, light, moderate, aggressive moderate Homoglyph replacement level
framing fiction, study_guide, academic, documentation, translation, none study_guide Narrative framing strategy
max_pieces 1–20 10 Max sub-query decompositions
padding_tokens 0–10000 5000 Long-context padding per query
multi_agent true, false true Multi-agent orchestration
helper_enabled true, false true Helper model with filters removed

Project Structure

evalkit/
├── evalkit/             # Core modules
│   ├── splitter.py      # Query → sub-questions
│   ├── encoder.py       # Unicode homoglyph engine
│   ├── wrapper.py       # Narrative wrapping
│   ├── api_client.py    # API client + model routing
│   ├── merger.py        # Output stitching + metrics
│   ├── context_builder.py  # Multi-turn conversation
│   ├── agent_router.py  # Agent pack coordination
│   └── models.py        # Data classes + enums
├── evalkit_server.py    # MCP server (FastMCP)
├── run.py               # CLI wrapper (no MCP needed)
├── benchmark.py         # Test matrix runner
├── tests/               # Pytest test suite
├── docs/                # Documentation
├── .mcp.json            # Claude Code auto-discovery
└── CLAUDE.md            # Claude Code instructions

Research Techniques

See docs/TECHNIQUES.md for detailed documentation of each technique.

References

License

MIT — authorized security research and defense evaluation only.

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