mcpField
H
HireMe MCP

HireMe MCP

Remote
mcp.djaouad.techBusiness & Marketing1Updated 3w ago
RepositoryVisit website

About HireMe MCP

HireMe MCP is an MCP server that lets AI agents inspect Djaouad Frih’s profile, work, pricing, and availability, then submit a project brief. It combines portfolio information with a brief intake flow.

Key features

  1. 01Profile and availability lookup
  2. 02Search shipped projects
  3. 03Fixed-price services and ETAs
  4. 04Next booking slot lookup
  5. 05Submit and persist project briefs

Use cases

  1. 01Check experience before hiring
  2. 02Compare service prices and timelines
  3. 03Find the next available booking slot
  4. 04Send project requirements through an agent

MCP support

Exposes profile, project search, pricing, availability, and brief-submission tools to MCP clients. Its endpoint uses Streamable HTTP.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://mcp.djaouad.tech/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

Tools

5

This tool takes no parameters.

Details

From the project README

HireMe MCP

The first portfolio AI agents can hire. An open Model Context Protocol server that exposes Djaouad Frih's real profile, shipped products, fixed pricing and a project-brief intake — so Claude, Cursor, ChatGPT or any MCP client can vet the work and file a brief on your behalf.

Live: https://mcp.djaouad.tech · MCP endpoint: https://mcp.djaouad.tech/mcp

Tools

ToolTypeWhat it does
get_profilereadIdentity, stack, live products, availability, contact links
search_projectsreadSemantic-ish search over shipped projects (proof of experience)
get_pricingreadFixed-price services in USD with ETAs
get_next_slotreadAvailability status + direct booking link
submit_project_briefwriteFiles a project brief → persisted + emailed. Rate limited per IP

The famous flows

  1. Founder delegate — "Claude, find me an AI engineer under $2k and send them my requirements" → their agent calls get_pricing → search_projects → files a brief.
  2. Recruiter deep-dive — "Has he actually shipped RAG?" → grounded answers with demo links.
  3. Comparison shopper — pricing + timeline vs. an agency, plus next opening.

Structure

backend/    Express + @modelcontextprotocol/sdk (Streamable HTTP, stateless)
            POST /mcp            ← MCP clients
            /api/tools/:id       ← same handlers over REST (widget, mobile)
            /api/briefs          ← admin inbox (Bearer ADMIN_TOKEN)
            /widget.js           ← embeddable badge
frontend/   Next.js console (Netlify → mcp.djaouad.tech): connect configs,
            live playground, scenarios
mobile/     Expo app: profile, tool runner, admin briefs inbox

Run locally

cd backend  && npm i && npm run dev        # :4343
cd frontend && npm i && npm run dev        # set NEXT_PUBLIC_API_URL=http://localhost:4343
cd mobile   && npm i && npm start          # Expo Go

Copy backend/.env.example → .env. Without DATABASE_URL it runs in memory-only demo mode; without Gmail creds email notifications are skipped silently.

Deploy

  • Backend → Render: render.yaml included (free tier). Set DATABASE_URL, ADMIN_TOKEN, optional GMAIL_USER/GMAIL_APP_PASSWORD.
  • Frontend → Netlify: repo import picks up netlify.toml (static export). Attach custom domain mcp.djaouad.tech.
  • Mobile → APK: eas build -p android --profile preview or expo run:android.

Connect in one paste

{ "mcpServers": { "hireme-mcp": { "url": "https://mcp.djaouad.tech/mcp" } } }

Built by Djaouad Frih — this server is itself the demo of what he ships.

Demo

HireMe MCP landing

MCP playground

Demo video: MCP flow

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.