cooklang-mcp-server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@cooklang-mcp-server search my recipes for chocolate cake"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
cooklang-mcp-server
A small FastMCP server that exposes the
CookCLI recipe server (cook server, as shipped in
ghcr.io/cooklang/cookcli) to a coding agent as MCP tools. With it, an agent can
browse, read, write, delete and search Cooklang recipes
over the CookCLI HTTP API.
Do you need this?
Use this server when the recipes are reached over HTTP: a cook server
running on another machine or on a NAS, or an MCP client such as Claude Desktop
that has no shell access.
If your recipes are local files and the agent can run commands (Claude Code,
Codex), the official
cooklang-skills plugin is the
better fit. It drives the cook CLI directly and covers more ground: meal
planning, pantry tracking, aisle-grouped shopping lists, exports.
Related MCP server: mealie-mcp
How it works
Each MCP tool maps 1:1 to a CookCLI HTTP endpoint (read_recipe -> GET /api/recipes/{path}, and so on). This server is a stateless adapter: it holds no
data, does no parsing, and requires a separate cook server process to be
running (see Requirements). All recipes live in CookCLI's recipe
directory.
Tools
Tool | Maps to | Purpose |
|
| Full recipe tree (folders + |
|
| One recipe parsed into ingredients, cookware, timers, steps |
|
| Raw Cooklang source, frontmatter included |
|
| Create or overwrite a recipe from raw Cooklang text |
|
| Permanently delete a recipe file (no undo, no trash) |
|
| Full-text search over recipe names and content |
|
| Collection counts ( |
path is relative to the CookCLI server's recipe directory, e.g.
Dolci/bunet-piemontese (the .cook extension is optional). write_recipe
requires the parent folder to already exist and writes atomically (temp file +
rename). Title images are not writable over HTTP: drop them next to the .cook
file in the recipe directory (or Docker volume).
Requirements
Python >= 3.10 and uv
A running CookCLI server, e.g.:
docker run -d --name cooklang-cookcli-1 -p 9080:9080 \ -v cooklang_recipes:/recipes \ ghcr.io/cooklang/cookcli server --host 0.0.0.0 /recipesor, with CookCLI installed locally,
cook server ./my-recipes.
Register with Claude Code
No clone needed. uvx fetches, builds and caches the server straight from this
repo:
claude mcp add cooklang \
--env COOKLANG_SERVER_URL=http://localhost:9080 \
-- uvx --from git+https://github.com/alessmar/cooklang-mcp-server cooklang-mcp-serverOr in .mcp.json / ~/.claude.json:
{
"mcpServers": {
"cooklang": {
"command": "uvx",
"args": ["--from", "git+https://github.com/alessmar/cooklang-mcp-server",
"cooklang-mcp-server"],
"env": { "COOKLANG_SERVER_URL": "http://localhost:9080" }
}
}
}COOKLANG_SERVER_URL defaults to http://localhost:9080. Pin a version by
appending @<tag> to the git URL, e.g. ...cooklang-mcp-server@v0.1.0.
Local development
git clone https://github.com/alessmar/cooklang-mcp-server
cd cooklang-mcp-server
uv sync
COOKLANG_SERVER_URL=http://localhost:9080 uv run cooklang-mcp-serverNotes
The CookCLI server has no auth and open CORS: keep it on localhost or a trusted LAN.
/api/reloadis a no-op on current CookCLI: the server reads from disk on every request, so file changes made outside the API are picked up immediately.
License
MIT. See LICENSE.
Available Tools
7 toolscollection_statsA
Return collection counts (recipe_count, menu_count, pantry_* counts).
Inputs: no named parameters. Returns: object
delete_recipeA
Permanently delete a recipe file. There is no undo and no trash.
Inputs: path (required). Returns: object
list_recipesA
Return the full recipe tree: folders and .cook / .menu files.
Every node has children, name, path, recipe. recipe is null for a
directory and non-null for a file.
Inputs: no named parameters. Returns: object
read_recipeA
Read one recipe parsed into ingredients, cookware, timers and steps.
path: recipe path relative to the recipe directory, e.g. "Dolci/bunet-piemontese" (the .cook extension is optional). scale: multiply quantities by this factor during parsing.
Inputs: path (required), scale. Returns: object
read_recipe_sourceB
Return the raw Cooklang source text of a recipe, frontmatter included.
Inputs: path (required). Returns: result
search_recipesA
Full-text search over recipe names and content. Returns name + path.
Inputs: query (required). Returns: result
write_recipeA
Create or overwrite a recipe. source is raw Cooklang text.
The parent folder must already exist. A missing .cook extension is added automatically. Writes are atomic (temp file + rename).
Inputs: path (required), source (required). Returns: object
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 7 tools
Each tool targets a clearly distinct operation: listing the tree, reading parsed recipes, reading raw source, writing, deleting, searching, and getting stats. The only potentially similar pair, read_recipe and read_recipe_source, is disambiguated by the parsed-versus-raw distinction.
Most tools follow a consistent verb_noun snake_case pattern: list_recipes, read_recipe, read_recipe_source, write_recipe, delete_recipe, search_recipes. collection_stats is the one outlier since it lacks a verb, but it remains readable and stylistically compatible.
Seven tools is well-scoped for a recipe management server. Each tool covers a meaningful part of the workflow without redundancy or unnecessary bloat.
The core recipe lifecycle is covered: discover, read, write, delete, and search. Minor gaps exist such as no folder creation tool and no dedicated menu management, but these do not block the primary recipe workflow.
Maintenance
Related MCP Connectors
Recipe search, ingredient matching, nutrition filters and a private cookbook for any AI agent.
Scraps Kitchen gives any AI agent a persistent, household-aware kitchen memory. Unlike generic chatbot recall, Scraps maintains structured cooking data: what's in your fridge (with freshness tracking), who you cook for (with allergens, dietary restrictions, and preferences), your recipe collection (with cook notes and per-diner ratings), your shopping list, and your kitchen equipment. 27 tools across 6 domains let agents read kitchen context, suggest meals that respect dietary safety, update the pantry after cooking, and build a history of what works for your household. Every interaction makes the data richer. Cooking history, preference signals, kitchen awareness = better suggestions next time. All tools work via oAuth and a free scraps.kitchen account.
Your Recipes, Beautifully Kept. weReci MCP server lets Claude and other MCP clients work with your personal weReci cookbook, the recipes you've imported from the web, social video and scanned family books. Interactive UI in the chat. weReci supports MCP Apps, so in clients that support it, tools return live views instead of plain text: recipe cards, shopping lists and your recipe graph. Clients without MCP Apps support get the same results as text. Find and read recipes: search your collection in plain language, open any recipe in full, or get an overview of what's in your cookbook. Cook with them: scale a recipe to any serving count, with cooking adjustments as well as amounts. Get substitution suggestions with ratios and caveats. Explore connections: browse your recipe graph (shared ingredients, techniques and cuisines), trace the connection between two recipes, and look up where a dish sits on the cuisine map. Themed collections: list the themed groups weReci curates from your cookbook, or ask it to reshuffle them. Shop: build a shopping list from one or more recipes, add or update items, and read the list back. Share: email a recipe to someone. Longer jobs like conceit reshuffles run in the background, with tools to check their progress. Everything is scoped to your own cookbook, or to a shared one you've joined.
Search, read, download and report on tested step-by-step recipes (playbooks) for AI agents.
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