culprit
This server provides MCP tools for root-cause analysis, fix verification, and risk assessment of code changes.
Full RCA in one call:
analyzeclassifies the change, finds suspect commits or blast radius, scores risk, and lists test impact.Verify a fix before committing:
verify_fixchecks a proposed diff for completeness, missed call sites, test coverage, and risk level.Find suspect commits:
find_suspectsranks commits likely to have introduced a bug, optionally from a stack trace.Check fix completeness:
check_completenessfinds untouched references to changed symbols.Get change intent:
get_intentreturns commit body, linked PR, and referenced issues.Trace line evolution:
get_evolutionshows every commit that touched a line range viagit log -L.Assess risk:
get_risk_scorereturns a 0-100 score with contributing factors.Map blast radius:
get_blast_radiusshows dependents, covering tests, and high-risk areas.Select tests:
get_test_impactfinds tests affected by a change.Classify changes:
classify_changedetermines bugfix vs feature with evidence.RCA from stack traces:
from_traceparses a crash log and returns suspects without a diff or PR.
Provides root-cause analysis for Git repositories: blames changed lines to find suspect commits, traces line evolution, maps blast radius, and verifies that a fix is complete before committing.
Integrates with GitHub pull requests to scope analysis to a PR's own base and head, retrieve PR metadata and linked issues, and act as a CI gate that fails on high QA risk.
culprit
Why an agent needs this
An agent can dig through git history to find what broke, and it is good at it. What it will not reliably do is spend a dozen tool calls on that every time, or stop and check whether the helper it just changed has three other callers before it commits. culprit turns both into one deterministic call that returns structured JSON it can act on:
The agent asks | culprit answers |
"What introduced this bug?" | Ranked suspect commits, the author's intent, the releases it shipped in |
"Is my fix complete?" |
|
"What could this change break?" | Reverse-import dependents, covering tests, high-risk shared modules |
⚡️ Instant. No test runs, no bisect. Benchmarked at 41% fewer agent tool calls.
🔒 Read-only and offline. Never writes to your repo or PR. No API key, no network.
🔌 MCP-native. 11 tools over stdio, on the official MCP registry, plus a one-command plugin.
🗣️ Language-agnostic. Suspects work anywhere git does. Blast radius reads 12 language families.
Related MCP server: Task Agent MCP
Does it actually work?
Benchmarked against 50 real regressions, 25 from git and 25 from
systemd, where the introducing commit is known from each
fix's Fixes: trailer (author-verified ground truth). Given only the fix commit, culprit blames
the removed lines to rank the commits that introduced the bug.
Metric | Result |
Introducing commit ranked #1 | 50% (25/50) |
Introducing commit in the top-5 suspect set | 66% (33/50) |
Deterministic and offline, on large C codebases the engine has never seen. Reproduce with
python benchmarks/run.py, which clones the repos and scores every case.
But an agent can run git blame itself
It can, and it is good at it. So the honest question is not whether culprit is accurate, but whether it beats or helps an agent that has git and no culprit. Same 10 regressions, three arms, isolated so no arm can read the answer from the fix commit:
culprit alone | agent alone | agent + culprit | |
Introducing commit ranked #1 | 80% | 90% | 90% |
Introducing commit in top 5 | 90% | 100% | 100% |
Mean tool calls to get there | 1 | 14.9 | 8.8 (-41%) |
Mean tokens to get there | ~0 | 55,534 | 47,616 (-14%) |
The agent wins on accuracy, and culprit does not make it more accurate. What culprit does is get it there in roughly half the steps for about 8,000 fewer tokens per investigation. Tool calls dropped in 10 of 10 cases, tokens in 7 of 10. On the hardest case the agent needed 42 tool calls and 124k tokens alone, against 16 calls and 84k with culprit.
Those savings are already net of reading culprit's output, which is counted in the third column. culprit's own run is one deterministic call, no model, under a second.
So culprit is an accelerator for an agent, not a replacement for one, and not a smarter
blamer than one. Method, caveats (n=10, and this slice is easier than the full 50), and
reproduction: benchmarks/agent/.
Quick start
Claude Code plugin (installs the MCP server plus a skill that tells the agent when to use it):
/plugin marketplace add noordeen123/culprit
/plugin install culprit@culpritAny MCP client (Cursor, Windsurf, VS Code, Codex CLI, Zed, Continue, Cline, Amazon Q, Goose):
{
"mcpServers": {
"culprit": {
"command": "uvx",
"args": ["--from", "culprit[mcp]", "culprit-mcp"]
}
}
}CLI, no agent required:
uvx culprit # run from PyPI on demand
rca --verify-fix patch.diff # exit 0 if complete, 1 otherwiseNeeds Python 3.10+ and uv for the MCP server. The CLI runs on 3.9+.
The tools
Tool | What it answers |
| Full RCA in one call: classify, suspects or blast radius, risk, test impact |
| Is this diff safe to commit? |
| Rank the commits that introduced the bug |
| Call sites of the changed symbol the fix did not touch |
| The introducing commit's message, linked PR, referenced issues |
| Per-commit history of the buggy lines via |
| QA gate score (0 to 100, low/medium/high) with contributing factors |
| Feature impact: dependents, covering tests, high-risk files |
| Minimal test set to run for this change |
| Bugfix vs feature, with evidence |
| RCA straight from a stack trace, no diff or PR needed |
verify_fix, the pre-commit gate
The agent runs this on its own diff before committing:
verdict:completewhen no untouched call site is left behind,partialwhen one was missed,riskywhen risk is high. The verdict is the completeness axis; test coverage is the separate confidence axis onrisk_level.untouched_references: the exact files that still use the changed symbol. This is the list the agent goes and patches.skipped_symbols,adds_test,notes: what was too widely used to check, whether a test shipped, and what to do next.
Loop until complete, then commit. That is the whole idea.
CLI and CI
rca # current branch vs the configured base
rca --last # the latest commit only
rca --pr 16786 # a specific PR (uses the PR's own base)
rca --trace crash.txt # RCA from a stack trace, no fix or PR needed
rca --verify-fix patch.diff # check a diff before committing
rca --select-tests # print the tests to run for this change
rca --html report.html --open # a single self-contained HTML report
rca --pr 16889 --fail-on high # exit non-zero when QA risk is high
rca serve --repo /path # local web UI with a base pickerCI gate: risk via exit code only, no PR comments, no writes. Copy
examples/github-actions/culprit-pr.yml into
.github/workflows/:
- run: pip install "culprit>=0.3.0"
- env: { GH_TOKEN: "${{ github.token }}" }
run: rca --pr ${{ github.event.pull_request.number }} --fail-on highHTML report
--html writes one self-contained file. No CDN, opens offline, attaches to CI. It opens with the
verdict: a scored QA risk with the factors behind it, and the prime suspect with how long the bug
lived.
Then it reconstructs how the bug got there. Every commit that touched the buggy line, from creation through the commit that broke it (red, with the exact diff) to the fix (green):
vs git bisect
| culprit | |
Input | A reliable failing test | The fix diff (or a stack trace) |
Method | Checks out commits and runs the test | Blames the fix's lines plus |
Speed | Minutes (about log2(N) test runs) | Instant |
Output | First bad commit | Suspect set, intent, lifecycle, completeness, risk |
Confidence | Proof | Strong heuristic |
--bisect "<cmd>" runs a real bisect as an optional confirmation layer, in a throwaway
git worktree so your checkout is never touched. When the first failing commit matches the
blamed suspect, the report stamps it confirmed by git bisect.
Architecture
One normalized context in, one structured JSON result out. The only non-deterministic step is the optional LLM narrative, isolated behind an adapter so the engine runs with no API key.
Two lanes, one engine. Every module writes one slice of the result, so nothing cares whether
the target came from gh, the REST API, local git, or a pasted stack trace. Full module map:
docs/ARCHITECTURE.md.
Configuration
The base branch resolves in order: the --base flag, then CULPRIT_BASE, then .culprit.toml
(base = "origin/main"), then HEAD~1. --last forces the latest-commit view.
PR titles and labels use the GitHub CLI when present, or the unauthenticated REST API for public
repos (set GITHUB_TOKEN or GITLAB_TOKEN to raise limits). Deep links cover GitHub, GitLab,
Bitbucket, and Gitea. Blast radius reads imports across JS/TS, Python, Go, Java/Kotlin, Ruby,
C/C++, C#, PHP, Rust, Scala, and Swift.
Contributing
pip install -e ".[dev]" && pytestModule map and data shapes: docs/ARCHITECTURE.md. Publishing the MCP
server to the registries: docs/PUBLISHING.md. MIT licensed.
Available Tools
11 toolsanalyzeA
Full RCA in one call: classify -> suspects (bugfix) or blast-radius (feature) -> risk score -> test impact.
Returns the complete structured result. Use the individual tools to drill into specific signals.
Inputs: repo (required), pr, base, head.
check_completenessA
Is the fix complete? Find other references to changed symbols not touched by this fix.
Returns: {symbols: [...], other_call_sites: {...}, untouched_count: int, adds_test: bool, is_revert: bool, notes: [...]}
Inputs: repo (required), base, head.
classify_changeC
Classify whether a change is a bugfix or a feature, with evidence.
Returns: {verdict: "bugfix"|"feature"|"unknown", evidence: [...], signals: {...}}
Inputs: repo (required), base, head.
find_suspectsA
Find the commits most likely to have introduced a bug.
Pass trace_text (a stack trace / crash log) to run RCA from a runtime error with no diff needed. Otherwise diffs base..head to find suspects.
Returns: {suspects: [{hash, short, author, date, subject, pr_number, weight, lines}], origin_on_branch: bool, notes: [...]}
Inputs: repo (required), base, head, trace_text.
from_traceA
RCA from a stack trace or crash log; no diff or PR needed.
Parses the stack trace, blames the crashing lines in git history, and returns the suspect set. Works for Python, JavaScript, Java, and Go stack traces.
Returns: {suspects: [...], frames: [{file, line, func}], skipped_frames: [...], notes: [...]}
Inputs: repo (required), trace_text (required), head.
get_blast_radiusB
Map what a feature change affects: who imports the changed modules, covering tests, high-risk areas.
Returns: {dependents: {...}, covering_tests: [...], high_risk: [...], notes: [...]}
Inputs: repo (required), base, head.
get_evolutionA
git log -L over a line range: every commit that touched those lines, oldest to newest, with per-step diffs.
Returns: {steps: [{hash, short, author, date, subject, diff}], notes: [...]}
Inputs: file (required), repo (required), end_line (required), start_line (required), +1 more.
get_intentB
Commit body + the PR it came from (title, body, url) + linked issues (Fixes/Closes/Resolves #N).
Returns: {body: str, pr: {number, title, body, url} | null, linked_issues: [...]}
Inputs: repo (required), commit_hash (required).
get_risk_scoreB
QA risk score for a change: 0-100 with level (low/medium/high) and contributing factors.
Combines test gap, fix completeness, hotspot recurrence, blast radius, and churn.
Returns: {score: int, level: "low"|"medium"|"high", factors: [{name, detail, points}]}
Inputs: repo (required), pr, base, head.
get_test_impactA
Which existing tests should be run for this change.
Walks the reverse-import graph from changed files to tests that cover them directly or transitively (up to 2 hops).
Returns: {tests: [...], by_test: {test: [reasons]}, notes: [...]}
Inputs: repo (required), base, head.
verify_fixA
Check fix completeness against a raw unified diff before committing.
Runs completeness + test-impact analysis on the proposed diff and returns a verdict. Iterate until verdict == "complete" (no untouched call sites). "complete" covers the root cause but does not imply a test exists - a complete but untested fix comes back at risk_level "medium" with a note, so check risk_level/notes and add the test before committing.
Returns: {verdict: "complete"|"partial"|"risky", symbols_fixed: [...], untouched_references: [...], tests_to_run: [...], adds_test: bool, risk_level: "low"|"medium"|"high", notes: [...]}
Inputs: repo (required), proposed_diff (required), base.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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TDQS
Scored across 11 tools
Several tool pairs have overlapping responsibilities: from_trace and find_suspects both take a stack trace and return suspects, verify_fix and check_completeness both assess fix completeness, and get_test_impact/get_blast_radius both surface covering tests. The descriptions are detailed, but an agent could easily select the wrong tool for the same underlying task.
Most names are lowercase snake_case verb_noun, but the verbs are inconsistent across get_, classify_, find_, check_, verify_, and two tools break the pattern entirely: from_trace and analyze. The naming is readable but not predictable enough to be considered a consistent convention.
Eleven tools is within a reasonable range for a change-analysis server, but the set is slightly larger than necessary because some tools duplicate or wrap each other's functionality. It is not bloated, just a bit redundant.
The tool surface covers the full RCA workflow: classify, identify suspects, map blast radius, compute test impact, score risk, verify completeness, inspect evolution, and read intent. The analyze tool also provides an orchestrated end-to-end path, while individual tools allow drilling into specific signals without obvious dead ends.
Maintenance
Related MCP Connectors
Change-aware CI validation and affected-test guidance for coding agents.
Guardian agent for AI coding: four frontier models review risky diffs and commits before they ship.
Visual testing for coding agents: your agent sees every UI change it makes and triages each diff.
Browser-backed QA with evidence and fix-ready reports for coding agents.
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