GitHub
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Description from the maker (original English)
Sandboxed test runs for coding agents: compact typed verdicts with failure fingerprints and history
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We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
VERDICT_PROJECTYou need
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Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"verdict": {
"command": "uvx",
"args": [
"verdict-mcp"
],
"env": {
"VERDICT_PROJECT": "your-value"
}
}
}
}Run this in your terminal
claude mcp add verdict --env VERDICT_PROJECT=your-value -- uvx verdict-mcpFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"verdict": {
"command": "uvx",
"args": [
"verdict-mcp"
],
"env": {
"VERDICT_PROJECT": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"verdict": {
"type": "stdio",
"command": "uvx",
"args": [
"verdict-mcp"
],
"env": {
"VERDICT_PROJECT": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
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VERDICT_PROJECT envThese settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
The registry name was verified with the GitHub account Dgotlieb, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
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It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.1.0a4) reached the registry 2 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
In the same category: GitHub, Desktop Commander, Cloudflare MCP
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
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Structured, sandboxed verification feedback for coding agents.
An MCP server that replaces your agent's pytest shell-outs with something built for the agent inner loop: impact-selected tests, run in an isolated environment, returning compact typed verdicts instead of 40,000 tokens of raw runner output — with failure fingerprints that tell the agent whether a failure is *its* regression or was broken all along.
raw pytest dump: ~40,000 tokens, unstructured, run un-sandboxed on your machine
verdict: ~400 tokens, typed JSON, run in a rootless container, with memory
The highest-frequency tool call in agentic coding is verification — and it's the least structured. Agents re-run whole suites when one module changed, burn context parsing ANSI-coded tracebacks, run arbitrary code directly on your machine, and routinely misdiagnose pre-existing breakage as their own regression (then "fix" code that wasn't broken). verdict fixes all four.
| Tool | What it does |
|---|---|
verify(scope?, base?) | Selects tests affected by your working-tree diff (static import graph via grimp), runs them via podman/docker with the worktree mounted read-only, returns typed failures with fingerprints and a preexisting flag |
explain_failure(check_id) | Full traceback for one failure, on demand — bulk never rides in the summary |
history(fingerprint) | First seen / last seen / times seen — regression vs. long-standing breakage |
run_checks(["ruff","mypy"]) | Lint and type checks, normalized into the same verdict schema |
Every failure carries a fingerprint: a stable hash of the normalized failure signature (volatile tokens — addresses, tmp paths, ids, durations — collapsed). Same logical failure, same fingerprint, across runs and refactors. Fingerprints are what give verdict memory.
No install step needed — uvx fetches it on first use. (Or uv tool install verdict-mcp / pip install verdict-mcp for a permanent verdict-mcp command.)
Claude Code — .mcp.json in your project root:
{
"mcpServers": { "verdict": { "command": "uvx", "args": ["verdict-mcp"], "env": { "VERDICT_PROJECT": "." } } } }
Cursor — same shape in .cursor/mcp.json.
Optional verdict.toml in your repo root:
[project]
packages = ["your_package"] # for impact selection (auto-guessed if omitted)
[runner] image = "ghcr.io/you/yourproj-test" # prebuilt env with your deps setup_cmd = "pip install -e .[test]" # or install on the fly (runs with network; tests don't)
[limits] max_failures = 10
Try it without an agent:
cd examples/demo_project
VERDICT_PROJECT=. verdict-mcp # then connect any MCP client, or use the MCP inspector
Checks run in an ephemeral container (podman preferred, docker fallback): worktree mounted read-only at /src, copied to a writable /work inside the container, --network=none for the check run. Your host environment is never mutated by a test run. If setup_cmd is configured, that step runs *with* network before the check; prefer a prebuilt image for a tighter posture. No container runtime → explicit prefer = "local" fallback runs checks against a temp copy of your worktree (still never in place). See SECURITY.md for the full threat model and known limitations.
Troubleshooting: if a verdict says container engine 'podman' could not start the check, run the suggested podman pull by hand — the engine's own error is the answer. One known trap on macOS: a "credsStore": "gcloud" line in ~/.docker/config.json makes podman call the gcloud credential helper for *every* registry, including docker.io; an expired gcloud login then breaks all pulls. Fix with gcloud auth login or remove that line.
verify(scope="all") is always available and verdict says in selection_note whenever it falls back.go test -json adapters are the most-wanted contributions (CONTRIBUTING.md).v0.2: coverage-based impact maps (precise selection), flake detection via fingerprint alternation, devcontainer.json support, result cache keyed on (tree hash, check, image digest). Later: vitest/jest, go test, cargo test adapters; per-repo verdict daemon mode.
Apache-2.0