Search Your Entire Codebase Using Connectors.
Code indexed, patterns detected, architecture documented, onboarding guides generated , build a living knowledge base from your codebase
Works with every AI agent you already use
…and any MCP-compatible client
Waiting for input…
Gemini How It Works
Your AI agent reads the GitHub repository structure: 4 services , auth-service (Go), payments-api (Node.js), web-app (React), worker (Python). It reads key files: README.md, main entry points, configuration files, and API route definitions.
For auth-service, it reads `main.go`, `routes.go`, `middleware/auth.go` , maps the request flow from entry to response. For payments-api, it reads `server.ts`, `routes/index.ts`, `services/stripe.ts` , identifies the Stripe integration pattern.
The agent indexes these patterns into Weaviate: service boundaries, API endpoints, shared patterns, dependency relationships. Now the codebase is semantically searchable: 'How does authentication work?' returns the auth middleware flow, JWT validation logic, and session management approach.
'What services talk to Stripe?' returns the payments-api integration with specific file paths. The agent then generates Notion documentation: an Architecture Overview page with service diagrams described in text, an API Reference with every endpoint, an Onboarding Guide with 'start here' instructions for each service.
The documentation is generated from code, not from memory.
Connector Orchestration: 3 Connectors, one intelligent agent
Connect GitHub, Weaviate and Notion Connectors so your AI agent reads your repositories, indexes code patterns and architecture into a Weaviate vector database for semantic search, and generates structured documentation pages in Notion. Engineering teams with poor documentation or fast-growing codebases get an auto-generated architecture guide that stays current. No documentation sprints. No outdated wikis. One prompt and your codebase has a searchable knowledge base.
Github
triggerReads repository structure, file contents and code patterns
get_file_contents search_github_code list_user_repositories get_repository_details Weaviate
actionStores code embeddings for semantic search across the codebase
get_full_schema list_objects get_object_details get_class_schema Notion
actionCreates architecture docs, API guides and onboarding pages
create_page query_database search_pages update_page_title Run This Automation Today
Connect Claude, ChatGPT, Cursor, or any AI agent to the Vinkius catalog and run this automation in minutes.
Build Your Own Connector
Convert any internal API into a Connector. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on each call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Connect & Automate
The 3 servers this recipe uses are ready in the catalog. Connect them once, paste a prompt, and your AI runs the full workflow.
- Github, Weaviate & Notion ready in the catalog right now
- Add more from 5,800+ servers whenever you need
- Connections are secured and compliant by default
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers and recipes added weekly
Superpowers you didn't know your AI had
The Vinkius catalog gives your agent access to 5,800+ Connectors and the intelligence to combine them. Imagine never logging into another dashboard. Your AI handles the work across all tools, in one conversation. That's what this connectivity layer was built for.
Cross-Platform Intelligence
Your agent doesn't just connect to tools. It understands the relationships between them. Data flows where it needs to go, automatically, with full context preserved across all platforms.
Contextual Reasoning
Each decision your agent makes considers the full picture. It reads CRM data, checks calendars, reviews conversation history, and acts on everything at once. Not step by step. All at once.
Productivity at Scale
What used to take 45 minutes across five different dashboards now takes one sentence. Your agent runs the entire workflow end to end while you focus on decisions that actually matter.
Zero-Config Reliability
No API keys to paste. No webhooks to configure. No YAML to debug. Connect your Connectors once, and your agent handles the rest. Each time, without intervention.
Made for
exactly this
Your AI agent taps into the entire Vinkius AI Connectors to handle these for you. You describe what you need. It does the rest.
Engineering teams with poor or outdated documentation who need auto-generated architecture guides from the actual codebase
New hires who need a searchable knowledge base to understand how the codebase works without bothering senior engineers for a week
Tech leads responsible for multiple services who need a unified view of API endpoints, dependencies and integration patterns
Companies preparing for technical due diligence who need comprehensive codebase documentation generated quickly
Frequently Asked Questions About This Connector Orchestration
Which Connectors do I need for this workflow?
Three: GitHub, Weaviate and Notion. Connect all three to your AI client.
Does this work with Claude Desktop, Cursor or Windsurf?
Yes. Any AI client that supports the Model Context Protocol works , Claude Desktop, Cursor, Windsurf, Cline and others.
How does Weaviate help compared to GitHub code search?
GitHub search finds exact text matches. Weaviate enables semantic search , ask 'How does error handling work?' and find relevant patterns even if they don't contain those exact words.
Does the documentation stay current?
Run the prompt weekly or after major changes. The agent re-reads the codebase and updates the Notion pages with current information.
Can I use GitLab instead of GitHub?
Yes. Replace the GitHub Connector with the GitLab Connector. The agent reads repository files and structure the same way.
How many repositories can it analyze?
The agent processes repositories sequentially. For large codebases, start with core services and expand. Each repository takes 2-5 minutes depending on size.
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Find Codebase Duplications Using Connectors
Your codebase has 4 different implementations of date formatting, 3 versions of the retry logic, and 2 competing validation libraries , but nobody knows because grep only finds exact matches and these duplicates are semantic
Generate Error Postmortems Automatically via MCP
Errors captured, stack traces analyzed, root cause commits identified, postmortem docs generated , write incident reports without the pain
How Connectors Auto-Triage Bug Reports
New bugs detected, severity classified, sprint tickets created, team notified , triage your backlog without a standup
MCP Recipe for Code Review Time Analytics
Review bottlenecks detected, unreviewed PRs surfaced, reviewer workload balanced, team velocity measured , fix your code review process with data
Connectors used in this workflow
GitHub
GitHub MCP lets you manage your entire software development lifecycle through a chat interface. You can check the status of a pull request, list open issues, or search for specific code snippets without ever leaving your primary workspace. It gives your AI agent direct access to your repositories, making it easier to audit codebases or update project statuses on the fly.
Weaviate
Weaviate MCP lets you manage your vector database and perform semantic searches directly through your AI client. It connects your Weaviate instance to your agent so you can query data by meaning rather than just keywords. It handles everything from checking cluster health to pulling specific object details or inspecting your full schema.
Notion
Notion MCP lets your AI agent read, search, and update your Notion workspace. It turns static docs into a live database your agent can query to find project specs, manage tasks, and update team pages instantly. This makes your company knowledge searchable and actionable from any MCP-compatible client.