# ForkMate (remote · mcp.forkmate.ai)

Effortless calorie tracking for people who train — just tell your AI what you ate.

- Trust score: 79/100 (medium)
- Change this week: +8
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-08-03

## Components

- remote · `mcp.forkmate.ai`: 79/100 (this document), [markdown](https://verifymcp.io/servers/ai-forkmate-forkmate/mcp.md), [page](https://verifymcp.io/servers/ai-forkmate-forkmate/mcp)

## Channel facts

- Endpoint: `https://mcp.forkmate.ai/`
- Transports: `streamable-http`
- Auth: `none`
- Version: `0.1.3`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-08-03.

- **Endpoint Security**: 97/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - Authorisation is enforced on tool calls, advertised via RFC 9728 protected-resource metadata. Discovery is public, which costs nothing: no tool can be invoked without a token.
  - HTTPS is enforced; there's no plaintext access path.
  - The HSTS (Strict-Transport-Security) header is present.
  - DNSSEC check failed: this domain isn't protected by DNSSEC.
  - The authorisation server supports Client ID Metadata Documents, the current MCP client-registration mechanism.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 67/100
  - AI-judged instruction clarity (excellent).
  - Context-footprint check failed: tool/resource definitions use about 2588 tokens (~215/item across 12 items; 12 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 27/100
  - Stability observed for 8 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 95/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 84% of tool parameters carry a description.
- **Capabilities**: 60/100
  - Spec-recency check failed: implements MCP spec 2025-06-18; the latest is 2026-07-28.

## Install

### Claude

```bash
claude mcp add --transport http ai-forkmate-forkmate https://mcp.forkmate.ai/
```

### Codex

```toml
[mcp_servers.ai-forkmate-forkmate]
url = "https://mcp.forkmate.ai/"
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "ai-forkmate-forkmate": {
      "type": "remote",
      "url": "https://mcp.forkmate.ai/",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add ai-forkmate-forkmate --url https://mcp.forkmate.ai/ --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  ai-forkmate-forkmate:
    url: "https://mcp.forkmate.ai/"
```

### Other

```json
{
  "mcpServers": {
    "ai-forkmate-forkmate": {
      "type": "http",
      "url": "https://mcp.forkmate.ai/"
    }
  }
}
```

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-08-03 (score 79, +1)

No change was recorded against any check on this day. Stability & Change Management went from 23 to 27. That category is still filling its 30-day observation window: 7 days of observed history at the previous scan, 8 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-08-01 (score 78, +1)

No change was recorded against any check on this day. Stability & Change Management went from 17 to 20. That category is still filling its 30-day observation window: 5 days of observed history at the previous scan, 6 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-31 (score 77, +6)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-30 (score 71, −1)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-28 (score 72, +1)

No change was recorded against any check on this day. Stability & Change Management went from 3 to 7. That category is still filling its 30-day observation window: 1 days of observed history at the previous scan, 2 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-27 (score 71, +1)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-26 (score 70)

First indexed and scored.

## MCP tools (12)

### `whoami` (~18 tokens)

Diagnostic: returns the authenticated user id and scopes.

### `get_day` (~145 tokens)

Read the user's food diary for a day (entries + calorie/macro totals). SAFETY: all calorie and macro values here — including carbohydrates — are ESTIMATES (from USDA / Open Food Facts or the user's own entry), approximate and not lab-measured or per-batch. They are for general nutrition tracking ONLY. Do NOT use them for insulin dosing, carb-counting for a bolus, blood-glucose prediction, or any other medical decision, and do NOT compute a dose or glucose estimate from them. For anything medical, direct the user to the product's own label and their care team.

Input parameters:

- `local_date` (string): YYYY-MM-DD; defaults to today.

### `get_range` (~155 tokens)

Read the user's diary across a date range, with per-day calorie/macro totals. SAFETY: all calorie and macro values here — including carbohydrates — are ESTIMATES (from USDA / Open Food Facts or the user's own entry), approximate and not lab-measured or per-batch. They are for general nutrition tracking ONLY. Do NOT use them for insulin dosing, carb-counting for a bolus, blood-glucose prediction, or any other medical decision, and do NOT compute a dose or glucose estimate from them. For anything medical, direct the user to the product's own label and their care team.

Input parameters:

- `end` (string, required): YYYY-MM-DD (inclusive).
- `start` (string, required): YYYY-MM-DD (inclusive).

### `get_preferences` (~180 tokens)

Read the user's saved dietary preferences so you can tailor logging and suggestions WITHOUT re-asking every chat: their diet style, a structured list of allergies to avoid (the big-9 major allergens), foods they dislike, and a typical-portion note. IMPORTANT: the allergen list is self-reported and is NOT a safety guarantee — always tell the user to check ingredient labels themselves; cross-contamination and gaps in food data are not captured (see the returned allergy_disclaimer). The `allergies` field covers the major US allergens ONLY; a user may have an allergen outside it (e.g. mustard, celery, corn, mollusks, barley/rye) — ask about those directly. NEVER treat the `dislikes` list as an allergy: it is a taste preference to de-prioritize, never a safety exclusion.

### `log_meal` (~287 tokens)

Log what the user ate to their food diary. Parse the user's free text into items and, when you can, include estimated macros per item for accuracy. SAFETY: all calorie and macro values here — including carbohydrates — are ESTIMATES (from USDA / Open Food Facts or the user's own entry), approximate and not lab-measured or per-batch. They are for general nutrition tracking ONLY. Do NOT use them for insulin dosing, carb-counting for a bolus, blood-glucose prediction, or any other medical decision, and do NOT compute a dose or glucose estimate from them. For anything medical, direct the user to the product's own label and their care team.

Input parameters:

- `at` (string): ISO-8601 instant the meal was eaten; defaults to now.
- `items` (array, required)
- `local_date` (string): YYYY-MM-DD diary date; defaults to the user's local date (from their timezone). Pass this to log a meal on a different day.
- `meal` (string)
- `note` (string)
- `source` (string): Optional provenance for these items. After search_foods/lookup_barcode, pass the candidate's source class (e.g. 'usda' or 'off') so the diary shows it's grounded. Defaults to 'client' (your own estim…

### `update_meal` (~441 tokens)

Correct a food already logged to the user's diary — fix a wrong calorie/macro value, quantity, or name, or move an entry to a different meal. Identify the entry by its `id` and `local_date` (both from get_day) and the food by its `item_index` within that entry's items[]. Only the fields you send change; the macros you send are MERGED onto the existing ones (so sending just `kcal` leaves protein/carb/fat as they were). This overwrites the value IN PLACE — there is no history of the previous value. Editing never moves an entry to another day (to do that, delete and re-log). SAFETY: all calorie and macro values here — including carbohydrates — are ESTIMATES (from USDA / Open Food Facts or the user's own entry), approximate and not lab-measured or per-batch. They are for general nutrition tracking ONLY. Do NOT use them for insulin dosing, carb-counting for a bolus, blood-glucose prediction, or any other medical decision, and do NOT compute a dose or glucose estimate from them. For anything medical, direct the user to the product's own label and their care team.

Input parameters:

- `caffeine_mg` (number): Corrected caffeine content, in milligrams.
- `fluid_ml` (number): Corrected fluid/hydration volume, in millilitres.
- `id` (string, required): The entry id to edit (from get_day).
- `item_index` (number): Which food in the entry's items[] to edit (0-based). Required when changing a food's name/quantity/macros/caffeine/fluid; omit for an entry-level change (meal/note).
- `local_date` (string, required): YYYY-MM-DD diary date of the entry (from get_day).
- `macros` (object): Corrected macros — only the components you send are changed.
- `meal` (string): Move the entry to a different meal label.
- `name` (string)
- `note` (string)
- `quantity` (string): Portion as stated, e.g. '2' or '1 cup'.

### `delete_meal` (~272 tokens)

Delete a food from the user's diary — remove one food from an entry (by `item_index`), or the whole entry (omit `item_index`). Identify the entry by its `id` and `local_date` (both from get_day). This is a TRUE removal: the data is gone, with NO server-side tombstone and no undo. Deleting the last food in an entry removes the entry. Safe to retry — deleting something already gone is a no-op success. SAFETY: all calorie and macro values here — including carbohydrates — are ESTIMATES (from USDA / Open Food Facts or the user's own entry), approximate and not lab-measured or per-batch. They are for general nutrition tracking ONLY. Do NOT use them for insulin dosing, carb-counting for a bolus, blood-glucose prediction, or any other medical decision, and do NOT compute a dose or glucose estimate from them. For anything medical, direct the user to the product's own label and their care team.

Input parameters:

- `id` (string, required): The entry id to delete from (from get_day).
- `item_index` (number): Which food to remove (0-based). Omit to delete the whole entry.
- `local_date` (string, required): YYYY-MM-DD diary date of the entry (from get_day).

### `get_pantry` (~152 tokens)

Read the user's PANTRY — the foods they keep ON HAND (their staples), so you can suggest meals from what they actually have and pre-fill macros when they log one. Returns each item's name and, when the user saved them, macros (for the item's serving), a serving label, a `source`, and a short note. The pantry is the user's CURATED list of what they stock — separate from what they've logged (their diary) and from their frequents (what they log often). IMPORTANT: a `source` (e.g. 'usda') is the user's own CLAIM about where the macros came from, NOT a server-verified guarantee — treat it as a hint, never as certified.

### `add_pantry_item` (~291 tokens)

Add a food to the user's pantry, or UPDATE it if it's already there (matched by name, any casing) — e.g. 'add rolled oats to my pantry'. Only `name` is required; include `macros` (for one serving), a `serving` label, a `source`, and a short `note` when you know them, so a later log can reuse them. Re-adding the same food REPLACES its details (an upsert — it never creates a duplicate). Only pass a `source` you actually got from search_foods/lookup_barcode; an unrecognized value is recorded as the user's own estimate ('client'). This does NOT log a meal — it only curates the user's staples.

Input parameters:

- `macros` (object): Macros for ONE serving of this food, when known.
- `name` (string, required): The food to keep on hand, e.g. 'rolled oats'.
- `note` (string): Optional short note, e.g. 'the Costco tub'.
- `serving` (string): Serving label the macros are for, e.g. '1 cup' or 'per 100 g'.
- `source` (string): Where the macros came from, if grounded via search_foods/lookup_barcode (e.g. 'usda'). Defaults to your own estimate ('client'); unrecognized values are recorded as 'client'.

### `remove_pantry_item` (~87 tokens)

Remove a food from the user's pantry by name — e.g. 'take eggs off my pantry list'. This removes it from their on-hand STAPLES only; it does NOT delete anything from their food diary. Safe to retry — removing something that isn't in the pantry is a no-op success.

Input parameters:

- `name` (string, required): The food to remove from the pantry (any casing).

### `search_foods` (~327 tokens)

Search USDA FoodData Central and Open Food Facts for foods matching a query, returning candidates with macros and a `source` you can show the user. IMPORTANT: the macros are PER 100 g (see each candidate's `serving`) — scale them to the portion the user actually ate before logging with log_meal. A candidate MAY also carry `serving_grams`/`serving_label` for ONE household serving (e.g. 48 g / "1 frank") — when present, offer the user 'N servings' instead of asking for grams, but still scale the per-100 g macros to the resolved grams before logging. When you log a chosen candidate, pass its `source` to log_meal so the diary records real provenance (USDA/Open Food Facts) instead of an estimate. SAFETY: all calorie and macro values here — including carbohydrates — are ESTIMATES (from USDA / Open Food Facts or the user's own entry), approximate and not lab-measured or per-batch. They are for general nutrition tracking ONLY. Do NOT use them for insulin dosing, carb-counting for a bolus, blood-glucose prediction, or any other medical decision, and do NOT compute a dose or glucose estimate from them. For anything medical, direct the user to the product's own label and their care team.

Input parameters:

- `limit` (number): Max candidates to return (default 5, clamped to 1–10).
- `query` (string, required): Food to search, e.g. 'greek yogurt' or 'Chipotle chicken'.

### `lookup_barcode` (~233 tokens)

Look up a packaged food by its UPC/EAN barcode via Open Food Facts. IMPORTANT: the macros are PER 100 g (see `serving`) — scale to the portion eaten before logging with log_meal. It MAY also carry `serving_grams`/`serving_label` for one household serving — offer 'N servings' when present, still scaling the per-100 g macros before logging. Pass the returned `source` to log_meal to preserve provenance. SAFETY: all calorie and macro values here — including carbohydrates — are ESTIMATES (from USDA / Open Food Facts or the user's own entry), approximate and not lab-measured or per-batch. They are for general nutrition tracking ONLY. Do NOT use them for insulin dosing, carb-counting for a bolus, blood-glucose prediction, or any other medical decision, and do NOT compute a dose or glucose estimate from them. For anything medical, direct the user to the product's own label and their care team.

Input parameters:

- `upc` (string, required): UPC/EAN barcode, digits only (8–14 digits).

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/ai-forkmate-forkmate/mcp#diagnostics

## Score history

- 2026-08-03: 79
- 2026-08-02: 78
- 2026-08-01: 78
- 2026-07-31: 77
- 2026-07-30: 71
- 2026-07-29: 72
- 2026-07-28: 72
- 2026-07-27: 71
- 2026-07-26: 70

## Links

- Remote endpoint: https://mcp.forkmate.ai/
- Repository: https://github.com/shawnazar/forkmate
- Website: https://forkmate.ai/
- Changelog RSS feed: https://verifymcp.io/servers/ai-forkmate-forkmate/mcp/changelog.xml
- Changelog JSON feed: https://verifymcp.io/servers/ai-forkmate-forkmate/mcp/changelog.json
- HTML version of this page: https://verifymcp.io/servers/ai-forkmate-forkmate/mcp