$ loading_
Checks PR merge readiness by validating CI, approvals, conflicts, and freshness.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "mcp-merge-guard" yet — see the docs or source repo.
Please judge whether this PR is mergeable: check CI status, required approvals, conflicts, and branch freshness. Return the conclusion and blocking reasons.
Outputs a mergeable/not mergeable verdict plus failing checks and reasons.
Run a pre-merge gate check for this Pull Request. Judge only by CI, approvals, conflicts, and whether the branch is stale; do not infer anything else.
Returns pass/fail for the gate with per-check results.
List all merge blockers for the current PR: CI, approval count, merge conflicts, and branch freshness.
Outputs a blocker list so developers can fix issues quickly.
Developers can use it to quickly verify whether a PR meets basic merge requirements. It fits as a final gate after CI, approval, and conflict checks.
DevOps or code owners can use it to enforce a consistent merge policy and avoid missing approvals or stale branches. It helps teams keep a uniform quality bar before merge.
In busy repositories with many parallel contributors, it can block PRs with conflicts or incomplete status before merge. This reduces the risk of introducing unstable changes into the main branch.
It performs pre-merge gate checks for PRs, focusing on CI, approvals, conflicts, and branch freshness. Its job is to help determine whether a PR is safe to merge.
Based on the description, it relies on PR status information such as CI results, approval data, conflict state, and branch freshness. For exact integration details, see the source repository.
CI is only one part of it; it also considers approvals, conflicts, and branch freshness. In other words, it checks the overall readiness to merge, not just whether tests pass.
Validate commit metadata and repo safety before you push.
Validate AI-generated code against real codebases before bugs reach runtime.
Secure MCP servers with policy checks, redaction, access control, and audit logs
Enforce permissions, approvals, sanitization, and audit for AI agent MCP calls.
Analyze project architecture and detect similar code patterns for cross-language consistency.
Detect doc drift and verify claims for MCP tools deterministically.