Skip to main content
Glama

List Programming Languages

dev.code.languages
Read-onlyIdempotent

List all 71 programming languages and their IDs for code execution, with compiler/interpreter versions. Filter by language name to find specific entries.

Instructions

List all 71 available programming languages and their IDs for code execution. Common IDs: 71=Python 3.8, 63=JavaScript (Node.js), 62=Java, 54=C++ (GCC), 60=Go, 73=Rust, 51=C#, 46=Bash. Returns full list with compiler/interpreter versions (Judge0 CE)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filterNoOptional filter — substring match on language name (e.g. "python", "java", "rust"). Returns all 71 languages if omitted

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Goes beyond annotations by specifying the exact number of languages (71), the return format (full list with compiler/interpreter versions), and the backend system (Judge0 CE). This adds critical behavioral context not captured in readOnlyHint or idempotentHint.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two well-structured sentences: first states purpose and scope, second adds common IDs and return details. No redundant information; every sentence adds value. Front-loaded with the most critical information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Fully covers the tool's purpose, input, and output for a simple listing tool. Describes the optional filter and what the response contains (full list with versions). No gaps given the simplicity and presence of an output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema defines the filter parameter with a description; the tool description adds examples (e.g., 'python', 'java') and clarifies default behavior (returns all 71 languages if omitted). This enhances usability beyond the schema alone.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the verb 'List' and the specific resource 'all 71 available programming languages and their IDs' with a precise count. Distinguishes itself from sibling tools like dev.code.execute by focusing on language listing rather than execution.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides common IDs (e.g., 71=Python 3.8) as usage hints for code execution. Implicitly guides when to use (before dev.code.execute), but lacks explicit when-not-to-use or alternative tools. Still effectively communicates its role.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/whiteknightonhorse/APIbase'

If you have feedback or need assistance with the MCP directory API, please join our Discord server