clinic-frontdesk-mcp

Give your LLM a front desk.

An open-source MCP server that turns any MCP-compatible client — Claude Desktop, Claude Code, or your own agent — into an AI receptionist for a small medical clinic.

It handles the front desk: booking and rescheduling appointments, registering patients, taking pre-visit intake, sending reminders, and answering questions about timings, fees and location. The LLM is the brain; this server is the hands.

You:    Book Mr. Shah with Dr. Mehta tomorrow evening for a diabetes follow-up.
Claude: Dr. Mehta has 6:00, 6:30 and 7:00 PM open tomorrow. Which suits him?
You:    6 PM.
Claude: Booked — Rajesh Shah with Dr. Anjali Mehta on Mon 10 Aug 2026 at 6:00 PM,
        for diabetes follow-up. A reminder goes out 24 hours before. Reference #1.

You:    He's had a headache for three days, should he take something?
Claude: I can't advise on that one — it's best discussed with the doctor. Dr. Mehta
        has 11:00 AM free on Tuesday if you'd like to bring the visit forward.

You:    Cancel it, actually.
Claude: That's Rajesh Shah with Dr. Mehta, Mon 6:00 PM, diabetes follow-up.
        Shall I cancel it?          ← nothing has happened yet

Behind those four turns: a patient lookup, a live availability check, a transactional booking, a queued reminder, a clinical question routed away from the model's own opinion, and a destructive action held back for confirmation.

Here is the same conversation from the server's side — the tools the model reaches for, and what comes back. Every line was captured from a real session; nothing here is mocked up.

Why it's not just a CRUD wrapper

A calendar with tool descriptions bolted on gets the happy path right and the other paths wrong. The interesting work here is in the failure modes:

Related MCP server: MCP Medical Appointments Demo

What it will not do

This server handles logistics only. It has no clinical knowledge and is not a medical device.

• No clinical advice. Medical questions return the clinic's standard "please discuss this with the doctor" response, with an offer to book an appointment. This is enforced in code, not left to the model's judgement — see Clinical safety.

• No diagnoses stored. Intake records what the patient said, in their words.

• Confirmation before destructive actions. cancel_appointment does nothing without an explicit confirm=true; called without it, it returns a preview to read back to the caller.

Privacy

Patient data stays on the machine running the server, in a single SQLite file. There are no external calls in v1 unless you explicitly configure the optional Twilio adapter.

Logs go to stderr only (stdout is the MCP transport) and PII is redacted before anything is written: phone numbers are masked and names collapse to initials. The audit_log table records every write action in the same redacted form.

The database is not encrypted at rest. Store CLINIC_DB_PATH on an encrypted volume and treat that file as you would any other patient record.

Setting it up — no coding required

This server has no screen of its own. It plugs into an app you already talk to — Claude Desktop is the easiest one — and that app grows a set of front-desk abilities. You do the talking; it does the booking.

Setup is five steps and takes about ten minutes. Exactly one of them uses a terminal, and it's a single line you copy and paste.

1. Install Claude Desktop

Download it from claude.ai/download, install it like any other app, and sign in.

2. Install uv

uv is a small free tool that fetches and runs this server for you. It brings its own copy of Python, so there is nothing else to install.

Open a terminal — on a Mac press ⌘+Space, type Terminal, press Enter; on Windows click Start, type PowerShell, press Enter — then paste one of these and press Enter:

# macOS or Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

# Windows
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

Close the terminal window when it finishes. That's the last command you'll type.

3. Open Claude's settings file

In Claude Desktop, go to Settings → Developer → Edit Config. That opens a file called claude_desktop_config.json in a text editor. If you'd rather open it by hand, it lives at:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

• Windows: %APPDATA%\Claude\claude_desktop_config.json

4. Paste in the clinic

Replace everything in that file with the block below, then save. If the file already has other entries under mcpServers, add just the "clinic-frontdesk" section alongside them.

{
  "mcpServers": {
    "clinic-frontdesk": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/prashant-cr/Clinic-front-desk-MCP-server",
        "clinic-frontdesk-mcp"
      ],
      "env": {
        "CLINIC_DB_PATH": "/Users/you/clinic-data/clinic.db",
        "CLINIC_NAME": "Demo Family Clinic",
        "CLINIC_TIMEZONE": "Asia/Kolkata"
      }
    }
  }
}

Three things to change for your clinic:

Use a full path for CLINIC_DB_PATH, starting from the drive or your home folder. Claude Desktop doesn't start the server from any particular folder, so a short path like clinic.db ends up somewhere you won't find it.

5. Restart Claude Desktop

Quit it completely — ⌘+Q on a Mac, or right-click the taskbar icon and Quit on Windows; closing the window isn't enough — then open it again. The first launch takes a few extra seconds while uv downloads the server.

Check it worked

Look for the tools icon near the message box; clinic-frontdesk should be listed. Then just ask:

Who are the doctors at the clinic?

If you get three doctors and their hours back, you're done. The first run creates the patient file and fills it with a demo clinic — three doctors, four patients and a small FAQ — so you have something to practise on before real data goes in.

Pick the receptionist_system prompt in Claude's prompt menu to put it into a warm, careful receptionist frame of mind, with the safety rules already in place.

Talking to it

Plain sentences work. There are no commands to memorise.

Ask it a medical question and it won't answer one — it will point the caller to the doctor and offer an appointment. That's deliberate; see What it will not do.

If something goes wrong

Where your data lives

Everything sits in the single file at CLINIC_DB_PATH on your own machine. Nothing is uploaded anywhere. To back it up, copy that file — the way you'd copy a photo — and keep the copy somewhere safe and encrypted. To move to a new computer, install the server there and copy the file across.

Try it: a five-step demo

Start a conversation with the server connected and try these in order. The first run seeds a demo clinic with three doctors, four patients and a FAQ.

1. "Who are the doctors at the clinic and when do they work?" → list_doctors. Dr. Mehta (general practice, split morning/evening shifts), Dr. Iyer (pediatrics, 20-minute slots), Dr. Sheikh (dermatology, 45-minute consultations).

2. "What's open with Dr. Mehta next Monday evening?" → check_availability. Returns real bookable slots in clinic-local time, past ones excluded.

3. "Book Mr. Shah with Dr. Mehta tomorrow evening for a diabetes follow-up." → find_patient, then book_appointment. Read back the confirmation. A reminder is queued for 24 hours before. Try booking the same slot again — you will get the nearest alternatives instead of a bare failure.

4. "He's been tired in the afternoons for about two months, takes metformin 500mg twice daily, allergic to penicillin." → submit_intake. Then ask "what will the doctor see?" → get_intake returns a one-paragraph brief a doctor can read in ten seconds.

5. "Actually, can we move that to Wednesday morning? And what are your consultation fees?" → reschedule_appointment (old → new summary, reminder re-queued) and answer_faq.

Then try the guardrails:

• "He's had a bad headache for three days — should he take something for it?" → the doctor redirect, not advice.

• "Cancel his appointment." → a preview and a request to confirm. Nothing is cancelled until you say yes.

• "What's the wifi password?" → match: none, so the agent offers to check with the front desk rather than inventing an answer.

For developers

# Run straight from the repository, no clone needed
uvx --from git+https://github.com/prashant-cr/Clinic-front-desk-MCP-server clinic-frontdesk-mcp

# Or clone and install
git clone https://github.com/prashant-cr/Clinic-front-desk-MCP-server
cd Clinic-front-desk-MCP-server
uv pip install -e .

# With the optional SMS adapter
uv pip install -e '.[twilio]'

Requirements: Python 3.11 or newer, and nothing else — SQLite is created and seeded on first run.

Not yet on PyPI. Until the first release, use the git forms above. After publication, uvx clinic-frontdesk-mcp becomes the one-line install and the config args shorten to ["clinic-frontdesk-mcp"]. If you cloned the repo, point command at /path/to/repo/.venv/bin/clinic-frontdesk-mcp with "args": [].

Other MCP clients

Any MCP-compatible client works — the server speaks stdio and nothing else. Claude Code:

claude mcp add clinic-frontdesk \
  --env CLINIC_DB_PATH=/absolute/path/to/clinic.db \
  --env CLINIC_TIMEZONE=Asia/Kolkata \
  -- uvx --from git+https://github.com/prashant-cr/Clinic-front-desk-MCP-server clinic-frontdesk-mcp

For other clients, give them the same command, arguments and environment variables as the JSON above in whatever format they use.

Tools

Read

Write

Every write appends a PII-redacted row to audit_log.

Configuration

All settings are environment variables, all with defaults — the server starts with no configuration at all.

Seeding happens only when the database file is created. Restarting never duplicates demo rows or resurrects deleted records. Set CLINIC_SEED=false to start empty for a real clinic.

How it works

  caller ──▶ Claude Desktop / Claude Code / your agent      ← the brain: language, judgement
                       │  MCP over stdio
                       ▼
             ┌───────────────────────┐
             │ server.py             │  14 tools, thin — no logic lives here
             ├───────────────────────┤
             │ scheduling  patients  │  slot maths, conflicts, intake
             │ faq         notifs    │  matching, clinical routing, reminders
             ├───────────────────────┤
             │ db.py  → clinic.db    │  SQLite on your disk. UTC in, local out
             └───────────────────────┘  every write mirrored to a redacted audit_log
                       │
                       └─▶ stderr (redacted logs)   ·   Twilio SMS (optional, off by default)

Nothing leaves the machine unless you configure the Twilio adapter yourself.

Time

Every timestamp is stored in UTC and every tool input and output is in clinic-local time. scheduling.py is the single conversion boundary — nothing above it touches UTC, nothing below it touches local time.

Slots come from a weekly template in schedules, overridden per-day by schedule_exceptions (a holiday closes the day; a time override replaces that day's windows). Slots that would run past the end of a window are dropped, so a 10:00–12:30 window in 20-minute slots ends at 12:20.

DST is handled explicitly: a slot at a wall-clock time that does not exist (spring forward) is skipped, and an ambiguous hour (fall back) is offered once. Slot durations are real elapsed time, so consecutive slots never overlap across a transition.

No double-booking

Two layers, because SQLite has no exclusion constraint:

1. A partial unique index on (doctor_id, starts_at_utc) for active appointments.

2. An overlap check and the insert inside one BEGIN IMMEDIATE transaction, which closes the check-then-insert race the index alone cannot cover for partial overlaps.

Clinical safety

Routing medical questions to the doctor is a rule, not a similarity score. Scoring failed it in both directions during development: "I have a bad headache for 3 days" fell below the escalation floor purely for being a long sentence, while the generic keyword take pulled "do you take insurance?" toward the medical entry.

A curated CLINICAL_TERMS vocabulary in faq.py now short-circuits to the redirect entry, which the seed marks with the reserved keyword medical. You can reword that answer for your clinic — just keep the keyword on it.

Development

uv venv
uv pip install -e '.[dev]'

uv run pytest -q                 # 248 tests
uv run ruff check . && uv run ruff format --check .
uv run mypy src/

Inspect the server with the MCP Inspector, pointing it at the installed entry point — the same command Claude Desktop runs:

# Interactive browser UI
npx @modelcontextprotocol/inspector .venv/bin/clinic-frontdesk-mcp

# Or drive it from the terminal
npx @modelcontextprotocol/inspector --cli .venv/bin/clinic-frontdesk-mcp --method tools/list
npx @modelcontextprotocol/inspector --cli .venv/bin/clinic-frontdesk-mcp \
  --method tools/call --tool-name list_doctors

Note that mcp dev src/clinic_frontdesk_mcp/server.py:mcp does not work here: it loads the file as a standalone module, which breaks the package-relative imports. Point the Inspector at the entry point instead, as above — it also exercises the real console script rather than a special-cased import.

Layout

src/clinic_frontdesk_mcp/
├── server.py         # MCP tool definitions only — thin, delegates everything
├── scheduling.py     # slot maths, conflict detection, the local<->UTC boundary
├── patients.py       # patient records and intake
├── faq.py            # FAQ matching and clinical-question detection
├── notifications.py  # reminder delivery adapters
├── db.py             # schema, migrations, seeding, redacted audit log
├── models.py         # domain dataclasses
└── config.py         # environment configuration

Business logic lives in the domain modules and is testable without MCP. If a tool body in server.py grows past a screen, the logic belongs somewhere else.

Not in v1

No web UI, no authentication or multi-tenancy, no real WhatsApp integration (the adapter interface is there), no EMR/FHIR integration, no payments, no multi-clinic support.

License

MIT — see LICENSE.