mcp-eval
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mcp-evalverify the candidate solution for the rounding-bug task and share the report"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP Agent Evaluation Harness
A compact reference project for evaluating coding agents that use Model Context Protocol tools. The harness gives an agent controlled repository access, runs repeatable checks, compares repeated executions, and returns a structured verification report.
What the project demonstrates
An MCP server with repository listing, reading, searching, and verification tools
Root-confined file access with traversal protection
Deterministic command execution with fixed locale, timezone, and Python hash seed
Required and forbidden code-pattern checks
Repeat-run comparison for nondeterminism detection
Golden reference material for a reproducible bug-fixing task
Standard-library unit tests and a continuous integration workflow
Related MCP server: phionyx-pipeline-mcp
Architecture
MCP client or coding agent
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v
Repository MCP tools
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v
SafeWorkspace boundary
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v
DeterministicVerifier
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v
Structured VerificationReportThe core verifier has no third-party dependency. The MCP adapter uses the official Python SDK v2.
Quick start
Run the unit tests.
python -m unittest discover -s tests -vRun the included evaluation task.
PYTHONPATH=src python -m mcp_eval_harness.cli verify \
examples/rounding-bug/task.json \
examples/rounding-bug/workspaceInstall the MCP adapter and start the stdio server.
python -m pip install -e ".[mcp]"
mcp-eval serveMCP tools
Tool | Purpose |
| Return a stable, sorted file list under the configured root |
| Read one UTF-8 file while blocking path traversal |
| Find literal text with deterministic ordering and result limits |
| Run the task specification and return a structured report |
Task specification
Each task is JSON and declares the files, code requirements, verification command, timeout, and repeat count.
{
"task_id": "decimal-rounding-fix",
"required_files": ["calculator.py", "test_calculator.py"],
"required_patterns": {"calculator.py": ["Decimal", "ROUND_HALF_UP"]},
"forbidden_patterns": {"calculator.py": ["round("]},
"command": ["python", "-m", "unittest", "discover", "-s", ".", "-p", "test_*.py"],
"timeout_seconds": 10,
"repeat_count": 2
}Security boundary
The path checks protect the configured repository root. The command verifier is designed for trusted local task definitions. Run untrusted candidate code inside a container or another operating-system sandbox.
Author
Mohammed Ibrahim Sadiq
License
MIT
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