mcp-units
Click on "Install 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., "@mcp-unitsconvert 240 ml to cups"
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.
MCP Cooking Units Converter
MCP Cooking Units Converter is a Python package and MCP server for converting cooking measurements (volume, weight, temperature) between common units. It is designed for integration with MCP-compatible tools and VSCode extensions.
Installation
Installing via Smithery
To install Cooking Units Converter for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @sellisd/mcp-units --client claudeManual Installation
Clone the repository:
git clone git@github.com:sellisd/mcp-units.git
cd mcp-unitsInstall:
uv pip install . # For normal use
# OR
uv pip install -e . # For developmentRelated MCP server: cook-mcp
Usage
Available Tools
The server provides the following conversion tools:
Volume Conversion
Convert between: ml, l, cup, tbsp, tsp
Example: 240ml → 1 cup
Weight Conversion
Convert between: g, kg, oz, lb
Example: 454g → 1 lb
Temperature Conversion
Convert between: Celsius (C), Fahrenheit (F)
Example: 180°C → 356°F
Running the Server
uvx --with . python -m mcp_units.serverUsing with VSCode Extensions
This MCP server can be integrated with VSCode extensions that support the Model Context Protocol. Here's how to set it up:
Install an MCP-compatible VSCode extension (e.g., Roo)
Configure the extension to use this server in
.roo/mcp.json:{ "mcpServers": { "units": { "command": "uvx", "args": [ "--with", ".", "python", "-m", "mcp_units.server" ], "disabled": false } } }
Contact
For questions, issues, or contributions, please visit the GitHub repository.
License
This project is licensed under the MIT License.
Available Tools
3 toolsconvert_temperatureA
Convert between Celsius (C) and Fahrenheit (F) temperatures
| Name | Required | Description | Default |
|---|---|---|---|
| value | Yes | Temperature value to convert | |
| from_unit | Yes | Source temperature unit (C or F) | |
| to_unit | Yes | Target temperature unit (C or F) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It accurately indicates a conversion operation but lacks details on rounding, precision, or edge cases. The simplicity of the tool mitigates the gap, but additional context would improve transparency.
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 a single, information-dense sentence that front-loads the key action and scope. Every word is necessary, with no redundancy.
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 conversion tool with three well-described params and no output schema, the description covers the essential purpose and scope. It could mention the expected behavior (e.g., reversible, precise) but is adequate for basic use.
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 description coverage is 100% (all three parameters have descriptions). The tool description adds no extra meaning beyond what the schema already provides, meeting the baseline for this dimension.
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 'Convert between Celsius (C) and Fahrenheit (F) temperatures,' specifying the verb (convert), the resource (temperatures), and the units. It implicitly distinguishes from sibling tools (convert_volume, convert_weight) by focusing on temperature units.
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?
No explicit guidance on when to use this tool vs alternatives, nor any mention of prerequisites, limitations, or when not to use it. The sibling tools handle different units, but the description does not address any decision criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
convert_volumeA
Convert between volume units (ml, l, cup, tbsp, tsp)
| Name | Required | Description | Default |
|---|---|---|---|
| value | Yes | Volume value to convert | |
| from_unit | Yes | Source volume unit (ml, l, cup, tbsp, tsp) | |
| to_unit | Yes | Target volume unit (ml, l, cup, tbsp, tsp) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the conversion operation but does not disclose any behavioral traits beyond that, such as precision, edge cases, or additional constraints. It is adequate but minimal.
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 a single, clear sentence that is front-loaded with the key verb and resource. Every word serves a purpose, with no wasted text.
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 conversion tool with a complete input schema and no output schema, the description sufficiently covers the purpose and units. It is slightly lacking in behavioral details but remains adequate.
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 description coverage is 100%, and the description merely lists the unit abbreviations already present in the schema enum. It adds no new meaning or clarity beyond what the schema provides.
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 the verb 'Convert' and the resource 'volume units', listing specific supported units (ml, l, cup, tbsp, tsp). It effectively distinguishes from sibling tools for temperature and weight conversions.
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 implies usage for volume conversions, and siblings (temperature, weight) provide contrast, but there is no explicit guidance on when to use this tool versus alternatives or any exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
convert_weightA
Convert between weight units (g, kg, oz, lb)
| Name | Required | Description | Default |
|---|---|---|---|
| value | Yes | Weight value to convert | |
| from_unit | Yes | Source weight unit (g, kg, oz, lb) | |
| to_unit | Yes | Target weight unit (g, kg, oz, lb) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must cover behavioral aspects. It does not mention any limitations (e.g., precision, range), side effects, or permissions needed. As a simple conversion, this is adequate but could be more informative.
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 a single sentence, very concise, and front-loads key information. It could be slightly expanded to include a mention of the output format without losing conciseness.
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 straightforward conversion tool with 3 fully described parameters and no output schema, the description is sufficient. It covers the basic purpose and supported units, omitting only minor details like return format.
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 coverage is 100% with detailed descriptions for each parameter. The description adds no additional meaning beyond what is already in the schema. Baseline 3 is appropriate.
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 the action ('Convert'), the resource ('weight units'), and lists the supported units explicitly. It distinguishes itself from sibling tools (convert_temperature, convert_volume) by specifying weight.
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?
No explicit guidance on when to use this tool vs. alternatives. While the name and description imply it's for weight conversion, there is no mention of when not to use it or references to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
3 tool updates
v0.3.3- First observed
convert_temperature - First observed
convert_volume - First observed
convert_weight
TDQS
Scored across 3 tools
Each tool handles a distinct type of unit conversion (temperature, volume, weight) with no overlap, making them easily distinguishable.
All tools follow the consistent 'convert_<unit_type>' pattern, using snake_case throughout.
Three tools is a reasonable count for a focused unit conversion server, covering common categories but not over- or under-scoped.
The server covers temperature, volume, and weight, but misses other common unit types like length, area, or pressure, leaving notable gaps for a general 'units' server.
Maintenance
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