Vectr MCP server
by swapnanilLets your AI code editor search your code by meaning and remember findings across sessions.
AI Library · 4,066 MCP servers
Lets your AI code editor search your code by meaning and remember findings across sessions.
Your AI can audit messy workspace files, recycle them safely, and undo any cleanup if needed.
Lets your AI check JSON, hash text, make UUIDs, test regex, convert dates and more, right in the chat.
Lets your AI check its own work against a strict checklist and keep an honest, tamper-evident record of what it decided.
Lets your AI read a tidy summary of your codebase so it writes code that fits your project.
Lets your AI send API requests, check responses, run saved tests, and compare environments for you.
Lets your AI trace how a business term or endpoint flows across services, from frontend to Kafka.
Lets your AI study your codebase's structure and suggest where changes belong.
Lets your AI check web links for safety, fix broken JSON, do math, and validate data before acting.
Lets your AI shrink big code files and messy logs so it uses fewer tokens and answers better.
Lets your AI check, test and review Deed code with the real compiler instead of guessing.
Your AI checks its own code changes for security and risky edits before saving them, and tells you what it fixed.
Lets your AI look up DNS records, reverse DNS, WHOIS and domain details for any website.
Lets your AI check whether a project's documentation still matches its code, and suggest fixes.
Stops your AI agents from double-charging or repeating the same action twice.
Snapshot your AI agent's behavior and get alerted when it quietly changes.
Lets your AI ask the Hirð compiler about types, actors, effects and supervision instead of guessing from source.
Search your code by meaning and see what calls what, all on your own machine.
Test how your MCP servers and AI agents behave when things go wrong, and get a reliability score.
Turn your AI's explanations into Mermaid diagrams you can view in your browser.
Lets your AI propose and look up your team's architecture decisions, while humans keep the final say.
Your AI can look at an error message, suggest a likely fix, and remember fixes that actually worked in your project.
Let your AI explore a SystemVerilog or Verilog chip design and trace signals without pasting code.
Lets your AI read your codebase's concepts, naming rules, and similar functions in one quick step.