RepoImmune MCP Server
Analyzes GitHub repositories and pull-request diffs to mine historical bug fixes, build regression checks, retrieve linked issues/PRs/commits/tests, and provide evidence for coding agents. Includes a read-only GitHub Action for PR analysis with SARIF and Markdown output.
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., "@RepoImmune MCP ServerCheck this patch against past regressions in the repo"
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.
RepoImmune turns a repository's resolved bugs into code-native, evidence-backed checks that can be queried by humans and coding agents.
Input | Processing | Output |
A GitHub repository or PR diff | Retrieve historical issue → fix → test → AST evidence | Exact regression location, source links, protected tests, and the historical fix |

60-second quick start
git clone https://github.com/Alex0AI/RepoImmune.git
cd RepoImmune
python -m venv .venv
# Windows: .venv\Scripts\activate
# macOS/Linux: source .venv/bin/activate
python -m pip install -e .
repoimmune init .
repoimmune check --diff examples/reintroduce-astropy-12907.diff --memory examples/memory
repoimmune replay astropy-12907 --memory examples/memory
repoimmune report --format htmlThe demo is offline, keyless, and dependency-free at runtime. The check intentionally exits 2 because it finds a real historical regression from Astropy PR #12907.
Related MCP server: cms mcp
What is executable memory?
A Behavior Card is not a chat summary. It binds an invariant to before/after code, AST form, exact symbols, regression tests, commits, source URLs, license, evidence class, and an optional replay capsule. RepoImmune refuses to promote a mined candidate when the evidence chain is incomplete.
flowchart LR
I[Issue / report] --> B[Buggy commit]
B --> F[Failing behavior]
F --> P[Fix PR / commit]
P --> T[Regression test]
T --> S[AST + symbol change]
S --> V[Repository invariant]
V --> C[Patch immunity check]The included vertical slice detects this exact reversion:
- cright[-right.shape[0]:, -right.shape[1]:] = right
+ cright[-right.shape[0]:, -right.shape[1]:] = 1It reports the precise line, explains why the all-ones block was historically wrong, links the issue/PR/merge commit, and names the pytest cases added with the fix.
CLI
repoimmune init .
repoimmune mine --repo owner/project
repoimmune check --diff HEAD~1
repoimmune recall "pagination returns duplicate rows"
repoimmune explain <behavior-card-id>
repoimmune replay <capsule-id>
repoimmune report --format html
repoimmune validate <card.json>check emits Markdown, JSON, or SARIF. mine saves conservative candidates only; it never calls an LLM and does not claim a Behavior Card from a title alone.
Agent and CI integrations
The composite GitHub Action analyzes pull-request diffs read-only and uploads SARIF/Markdown evidence.
The stdio MCP server exposes six structured, read-only tools:
search_past_failures,explain_code_history,check_patch_against_memory,list_invariants_for_file,get_regression_test, andreplay_behavior_case.The open Agent Skill asks an agent to recall history before risky edits and again before claiming completion. It grants no commit, push, merge, or test-bypass authority.
The static demo works without login or an API key.
Evidence classes
Every result is explicitly one of:
verified: directly replayed or mechanically corroborated with primary code/test evidence.externally_reported: trusted upstream or benchmark execution record, not reproduced here.heuristic: useful candidate or similarity signal, not proof.inconclusive: conflicting or incomplete evidence.
A similarity score is never presented as proof. Findings always show the matched code and source evidence.
Why this is different
Agent/chat memory: remembers conversations or repository facts; RepoImmune mines code history and creates mechanical checks that outlive any agent session.
SWE-bench: evaluates whether an agent can repair an issue; RepoImmune converts resolved issues into durable prevention assets.
Static analysis: starts from general rules; RepoImmune learns repository-specific invariants from that repository's real failures.
Test generation: may create tests; RepoImmune preserves the causal chain among report, buggy/fixed code, test, and invariant.
git blame: tells who and when; RepoImmune explains why behavior must survive and can check it.
See research-landscape.md for the evidence-backed comparison.
Security model
Issue text, PR comments, code, patches, and repository metadata are untrusted data. RepoImmune never evaluates them as instructions. Mining uses bounded HTTPS responses; refs and repository names are validated; capsule runs use fixed argv without a shell, reject absolute paths and symlinks, and time out. Unknown repositories' install scripts or tests are never run by default. See SECURITY.md and docs/threat-model.md.
Current scope and honest limits
The alpha deeply supports Python AST and pytest evidence. TypeScript/TSX has an optional pinned tree-sitter adapter for normalized structure and call extraction; JavaScript uses deterministic token structure, and Jest/Vitest can be recorded as test evidence. Whole-program interprocedural reachability, automatic upstream environment reconstruction, and broad language support are roadmap items. Dataset-scale cards are externally_reported until replayed; the bundled Astropy vertical slice is the only locally verified behavioral capsule in v0.1.0.
Reproducibility
python scripts/build_research_snapshot.py --limit 500 --cards 120
python scripts/run_experiments.py
pytest
coverage run -m pytest && coverage report
ruff check . && mypy src/repoimmuneAll published counts are regenerated into research/results.json; classifications and limitations are preserved, including unsuccessful or inconclusive cases. Data provenance lives in DATA_SOURCES.md, THIRD_PARTY.md, and research/data-card.md.
The committed v0.1 snapshot contains 500 candidates, 120 Behavior Cards, 12 repositories, and 30 lightweight structural capsules. On deterministic mutations it detected 120/120 exact historical reversions and 120/120 protected assertion deletions; same-symbol fixed-form refactors produced 9/120 false positives (7.5%). Title-derived retrieval reached Recall@5/MRR 1.0/1.0, but this is explicitly a same-source plumbing test. Independent mining precision and controlled Agent A/B remain inconclusive.
Contributing
Read CONTRIBUTING.md, the roadmap, and the Behavior Card schema before proposing a new miner or evidence source. Apache-2.0 licensed.
中文说明:README.zh-CN.md
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