food-recipe-mcp
Server Details
Semantic search across 50,000+ food recipes with hybrid retrieval and reranking.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- AIDataNordic/Food-Recipe-MCP
- GitHub Stars
- 0
- Server Listing
- food-recipe-mcp
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Tool Definition Quality
Average 4.7/5 across 2 of 2 tools scored.
The two tools, 'ping' and 'search_recipes', have completely distinct purposes: one is a connectivity test, the other is a recipe search. There is no ambiguity or overlap.
Both tools use lowercase names, and 'search_recipes' follows verb_noun pattern. 'ping' is a standard exception but still maintains a consistent style.
With only two tools, and one being a simple health check, the server feels underdeveloped for a recipe domain that typically includes multiple operations like getting a recipe by ID or filtering.
The server covers core recipe search well, but lacks other expected operations such as retrieving a specific recipe directly, listing cuisines, or user interaction features.
Available Tools
2 toolspingARead-onlyInspect
Simple connectivity test. Returns a greeting to confirm the server is running.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | Arbitrary label included in the response, e.g. 'healthcheck' | world |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotation already provides readOnlyHint=true, so the read-only nature is known. The description adds that it returns a greeting, which is behavioral context beyond the annotation. No contradictions. It could note that no state is modified, but the annotation covers safety.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: a single sentence that captures the purpose and output. Every word earns its place; there is no extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple ping tool with one optional parameter and existing output schema, the description covers all needed information: purpose, parameter usage, and response nature. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes the 'name' parameter with 100% coverage. The tool description adds 'Arbitrary label included in the response, e.g. 'healthcheck'', which provides usage context and an example, adding meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Simple connectivity test. Returns a greeting to confirm the server is running.' It uses a specific verb ('test') and resource (connectivity), and it distinguishes itself from the sibling tool 'search_recipes' which is for searching, not testing connectivity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly indicates when to use it: to test connectivity. It does not explicitly state when not to use it or mention alternatives, but the context of having only one sibling (search_recipes) makes it clear. A slight improvement could be an explicit condition, but it's adequate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_recipesARead-onlyInspect
Search a database of recipes using hybrid semantic search (dense + sparse) with reranking.
The database contains ~50,000 recipes from Food.com covering a wide range of cuisines, meal types, and cooking styles. Recipes include nutritional information, difficulty ratings, and user ratings.
Use natural language in the query to describe what you are looking for — cuisine, style, main ingredient, occasion, or mood all work well. Norwegian and English are both supported natively. Examples: 'quick Italian pasta for weeknight dinner' 'Swedish meatballs with gravy' 'healthy high-protein chicken bowl' 'easy chocolate cake for beginners' 'something with salmon and lemon' 'Indian curry chicken' 'traditional Norwegian kjøttkaker' 'hurtig pasta med kylling' 'enkel sjokoladekake'
Args: query: What you are looking for — describe the dish, cuisine, main ingredient, cooking style or mood freely. Any language is supported. diet: Optional — filter by dietary requirement: 'vegetarian', 'vegan', 'gluten-free', 'dairy-free', 'low-carb', 'keto', 'paleo' max_minutes: Optional — maximum total time in minutes, e.g. 30 difficulty: Optional — 'easy', 'medium' or 'hard' servings: Optional — not used for filtering (servings vary), but include in query for scaling context, e.g. 'pasta dish for 6 people' limit: Number of results to return after reranking (default 5, max 20)
Returns: List of recipes ranked by relevance. Each result includes rerank_score, rrf_score (hybrid fusion), title, total_time, difficulty, diet labels, ingredients, instructions, nutrition, rating, and source URL context.
| Name | Required | Description | Default |
|---|---|---|---|
| diet | No | Optional dietary filter: vegetarian, vegan, gluten-free, dairy-free, low-carb, keto, or paleo | |
| limit | No | Number of results to return after reranking (1–20, default 5) | |
| query | Yes | Natural language description of what you want, e.g. 'quick Italian pasta' or 'enkel sjokoladekake' | |
| servings | No | Not used for filtering — include serving size context in query instead, e.g. 'pasta for 6 people' | |
| difficulty | No | Optional difficulty filter: easy, medium, or hard | |
| max_minutes | No | Optional maximum total cooking time in minutes, e.g. 30. Use 0 for no limit |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations confirm read-only, closed-world. Description adds details on search method (hybrid semantic with reranking), return fields (ranked results with scores, ingredients, instructions, etc.), and clarifies that servings is not a filter. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with sections for description, examples, Args, and Returns. Concise yet comprehensive, every sentence adds value. Front-loaded with purpose and key features.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given complexity (6 params, 1 required, output schema exists), the description fully covers dataset, search behavior, parameter semantics, and return structure. No gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema descriptions cover all 6 parameters (100%), but the description adds substantial value: lists diet options explicitly, explains limit default/max, clarifies max_minutes meaning, and instructs to put serving context in query. Examples enhance understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches a recipe database using hybrid semantic search, specifies the database source (Food.com) and contents (~50k recipes with nutrition, difficulty, ratings). The only sibling is 'ping', so differentiation is inherent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance on query language (natural language, Norwegian/English), examples, and parameter usage. Lacks explicit when-to-use vs alternatives, but the sibling set is minimal so this is a minor gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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