GitKnecht automates code reviews, security scanning, issue triage, and wiki generation — all running on your own infrastructure.
GitKnecht integrates with your GitLab instance to automate the entire development workflow — from code review to documentation.
Every day, your team creates merge requests, files issues, and updates documentation. But code reviews get delayed, security vulnerabilities slip through, issues pile up unsorted, and your wiki becomes outdated the moment you push code. It's a full-time job just keeping everything in sync.
GitKnecht runs alongside your GitLab instance as a self-hosted service. It connects via the GitLab API, monitors your projects for new merge requests and issues, and deploys AI agents that work in the background — reviewing code, scanning for security issues, classifying and deduplicating issues, and keeping your wiki documentation automatically updated.
When you push code and create a merge request in GitLab, GitKnecht's polling service detects the change within seconds. It clones your project, analyzes the diff with an LLM-powered review engine, and posts structured feedback directly as an MR comment. Simultaneously, it scans open issues for duplicates using semantic tag matching, regenerates wiki pages that match changed files, and answers team questions grounded in your actual documentation.
Connects via GitLab API to monitor MRs, issues, and wiki changes in real-time.
Maintains a local database of projects, reviews, issues, and wiki pages for fast access.
Multiple specialized agents handle code review, security scanning, issue triage, and wiki generation.
All data stays on your infrastructure. API keys encrypted at rest. Zero data leaves your server.
Source of truth — projects, MRs, issues, and wiki pages
Monitors GitLab for new MRs and issues on configurable intervals
LLM-powered code analysis with multi-model fallback and structured output
Classifies issues, extracts semantic tags, deduplicates using fuzzy matching
Diff-aware regeneration keeps documentation synced with code changes
Documentation-grounded Q&A — ask questions, get answers from your wiki
Six AI agents working in concert to keep your codebase clean, secure, and well-documented.
Automated merge request reviews powered by LLMs. Detects bugs, anti-patterns, and quality issues with structured feedback — posted directly as MR comments.
Identifies vulnerabilities, hardcoded secrets, and dangerous anti-patterns in every diff. Your code stays secure without manual effort.
LLM-powered issue classification in any language. Automatic deduplication using semantic tag matching. Bugs and features sorted intelligently.
When code changes, your wiki updates automatically. Diff-aware regeneration keeps documentation in sync with your codebase.
Ask questions about your project and get answers grounded in your actual wiki documentation. Contextual, accurate responses.
Configurable polling supervisor with MR-level blocking prevents duplicate reviews. Multiprocessing pool scales to your needs.
Scans for potentially conflicting merge requests based on branch keywords and overlapping components. Know before you merge.
Supports multiple LLM providers (OpenAI, Anthropic, OpenRouter, Azure). Automatic fallback keeps reviews flowing.
All API keys and credentials are encrypted at rest. Your infrastructure secrets never leave your server in plaintext.
GitKnecht works silently in the background, automating the tedious parts of development.
Create a merge request in GitLab as usual. GitKnecht detects it via configurable polling or webhooks.
The review engine analyzes your diff with LLM-powered analysis, checking for quality, security, and best practices.
Open issues are classified, tagged, and deduplicated. No more duplicate bug reports or unsorted feature requests.
Changed files trigger wiki regeneration. Your documentation stays in sync with your codebase automatically.
Review the AI feedback, address any findings, and merge knowing your code has been thoroughly vetted by AI — all without leaving GitLab.