# ForkMate MCP server

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

## Links
- Registry page: https://www.getdrio.com/mcp/ai-forkmate-forkmate
- Repository: https://github.com/shawnazar/forkmate
- Website: https://forkmate.ai

## Install
- Endpoint: https://mcp.forkmate.ai/
- Auth: Not captured

## Setup notes
- Remote endpoint: https://mcp.forkmate.ai/

## Tools
- whoami - Diagnostic: returns the authenticated user id and scopes. Endpoint: https://mcp.forkmate.ai/
- get_day - 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. Endpoint: https://mcp.forkmate.ai/
- get_range - 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. Endpoint: https://mcp.forkmate.ai/
- get_preferences - 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. Endpoint: https://mcp.forkmate.ai/
- log_meal - 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. Endpoint: https://mcp.forkmate.ai/
- update_meal - 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. Endpoint: https://mcp.forkmate.ai/
- delete_meal - 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. Endpoint: https://mcp.forkmate.ai/
- get_pantry - 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. Endpoint: https://mcp.forkmate.ai/
- add_pantry_item - 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. Endpoint: https://mcp.forkmate.ai/
- remove_pantry_item - 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. Endpoint: https://mcp.forkmate.ai/
- search_foods - 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. Endpoint: https://mcp.forkmate.ai/
- lookup_barcode - 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. Endpoint: https://mcp.forkmate.ai/

## Resources
Not captured

## Prompts
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## Metadata
- Owner: ai.forkmate
- Version: 0.1.3
- Runtime: Streamable Http
- Transports: HTTP
- License: Not captured
- Language: Not captured
- Stars: Not captured
- Updated: Jul 4, 2026
- Source: https://registry.modelcontextprotocol.io