v0.1.0 · read-onlyno account · no key · nothing stored

Point your agent at me.

A stateless, read-only MCP endpoint that answers questions about Alex Chernysh from the same notes and case studies the site is built on. Four tools. Any MCP client. Nothing to sign up for.

Install

claude mcp add --transport http alex https://mcp.alexchernysh.com/mcp

{ "mcpServers": { "alex": { "type": "http", "url": "https://mcp.alexchernysh.com/mcp" } } }

curl -s https://mcp.alexchernysh.com/mcp -H 'content-type: application/json' -H 'accept: application/json, text/event-stream' -d '{"jsonrpc":"2.0","id":1,"method":"tools/list"}'

Tools

ask_alex	Ask a question about Alex Chernysh — background, projects, Bernstein, or working style. The answer is grounded in the published site content and declines questions it has no source for.
get_profile	Structured professional profile: identity, positioning, stack, and capabilities.
list_projects	Featured and additional projects, with a short description and a link where one exists.
get_cv	Link to the downloadable CV/résumé plus a short text summary.

60 requests/min · 64 kb body · stateless

One real call

get_profile · 144 ms

request

{
  "jsonrpc": "2.0",
  "id": 2,
  "method": "tools/call",
  "params": {
    "name": "get_profile",
    "arguments": {}
  }
}

response

{
  "result": {
    "content": [
      {
        "type": "text",
        "text": "Alex Chernysh — Applied AI Systems & Platform Engineer"
      }
    ],
    "structuredContent": {
      "name": "Alex Chernysh",
      "identity": {
        "name": "Alex Chernysh",
        "role": "Applied AI Systems & Platform Engineer",
        "base": "Tel Aviv, Israel",
        "languages": "English (fluent), Russian (native), Hebrew (conversational)",
        "contact": "alex@alexchernysh.com",
        "booking": "https://calendly.com/alexchernysh/15min",
        "github": "https://github.com/chernistry",
        "x": "https://x.com/alex_chernysh",
        "site": "https://alexchernysh.com"
      },
      "sections": [
        {
          "heading": "Positioning",
          "items": [
            "I build production AI systems — not demos. Agent platforms, tool-calling architectures, full-stack operator tools.",
            "The work happens after \"let's use AI\" and before anything actually works in production: grounding, evals, cost tracking, audit trails as first-class primitives.",
            "Strongest at agent orchestration, multi-agent coordination, MCP/A2A protocols, grounded retrieval, internal platforms, and eval-driven delivery."
          ]
        },
        {
          "heading": "What I Build",
          "items": [
            "Multi-agent coordination layers with worktree isolation, quality gates, and HMAC audit trails.",
            "Agent systems with clear tool contracts, approval boundaries, and observable state transitions.",
            "Retrieval and answer pipelines that cite, abstain, or escalate instead of improvising with confidence.",
            "Internal AI platforms that unify fragmented APIs, workflow automation, and operational visibility into a single operator surface.",
            "Spec-driven delivery loops that keep humans architectural while agents handle the mechanical bulk."
          ]
        },
        {
          "heading": "Flagship Open-Source Work",
          "items": [
            "Bernstein — the open-source governance layer for AI agents",
            "Creator and maintainer of Bernstein (https://bernstein.run, Apache-2.0, https://github.com/sipyourdrink-ltd/bernstein).",
            "Open-source governance layer for AI agents, built on a deterministic multi-agent scheduler, distributed on PyPI.",
            "Coordinates 40+ AI coding-agent adapters in parallel — Claude Code, Codex, OpenAI Agents SDK, Cursor, Gemini CLI, Aider, Amp, and more.",
            "What demo-grade multi-agent tools do not have: worktree-isolated execution, janitor verification, quality gates, HMAC audit trail, cost-aware model routing.",
            "Supports MCP and A2A protocols, Cloudflare cloud runtime."
          ]
        },
        {
          "heading": "Recent Systems Work",
          "items": [
            "Marketing operations CNS (case study)",
            "Sole engineer on a central operations platform built end-to-end in three months.",
            "Next.js + FastAPI + ClickHouse. Unifies real-time data from seven ad platforms and four revenue partners into a single AI-powered decision surface.",
            "Agentic AI advisor with three-tier tool-calling and MCP integration. Every answer grounded in live data via retrieval and citation gates. Anomaly detection, optimization recommendations, creative generation pipeline.",
            "Full product surface: kanban, notifications (in-app, push, email, Teams), RBAC, ChatGPT-style sharing. Became the team's primary daily operating tool.",
            "Public write-up: https://alexchernysh.com/blog/building-cns-marketing-operations",
…

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Stateless here means every call carries everything it needs: there is no session to open, no cookie to set and nothing kept once the response is written. The exchange above is the whole interaction — reload the page and it starts from the same place.