Skip to main content
Glama

OnlineCompiler.io

Server Details

Run Python, Java, C, C++, C#, Go, Rust and 5 more languages, each run in a fresh, offline sandbox.

Ownership verified
Status
Healthy
Last Tested
Transport
Streamable HTTP · MCP 2025-11-25
URL

TDQS

A4.1/5.0

Scored across 2 tools

Disambiguation5/5

list_compilers and run_code have clearly distinct purposes: one discovers available compilers, the other executes code. There is no overlap or ambiguity between them.

Naming Consistency5/5

Both tools use a consistent snake_case verb_noun pattern: list_compilers and run_code. The convention is predictable and readable.

Tool Count3/5

With only 2 tools, the server is minimal and borderline thin for a code execution service. The tools are well-scoped, but the surface feels very small even for the narrow domain.

Completeness4/5

The core workflow is covered: list compilers and execute code with optional stdin. Minor gaps exist, such as no compiler metadata beyond id/name and no file-based execution support.

Available Tools

2 tools
list_compilersList CompilersAInspect

List all available compilers/languages supported by OnlineCompiler.io.

Returns a list of compiler objects with id and name. Use the id value as the compiler argument when calling run_code.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A4.2/5.0
Behavior3/5

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

No annotations are provided, so the description must carry the behavioral burden. It does say it returns a list of objects with id and name, which is useful, but doesn't mention rate limits, auth requirements, or whether the list is static. Adequate but not rich.

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?

Three short sentences, front-loaded with the purpose and then the return shape and downstream usage. Every sentence earns its place.

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

Completeness4/5

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

There is an output schema, so return detail needn't be fully explained, but the description still adds the id/name shape and the linkage to run_code. It's complete enough for a zero-param, read-only listing tool.

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?

Zero parameters, so baseline is 4. The schema is empty and the description correctly implies no inputs are needed.

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?

States a specific verb (List) and resource (compilers/languages), and distinguishes itself from the sibling run_code by making clear this is the discovery step that feeds run_code.

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?

Explicitly tells the agent to use this tool and then pass the returned id to run_code, which is clear usage context. It doesn't state when-not-to-use, but for a simple discovery tool that's a minor gap.

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

run_codeRun CodeAInspect

Execute code in a sandboxed Docker container via the OnlineCompiler.io API.

Runs source code with the specified compiler and optional stdin input. Returns output, error, status, cpu time, and memory usage. Code execution is limited to 30 seconds and 512MB RAM.

ParametersJSON Schema
NameRequiredDescriptionDefault
codeYesThe source code to execute
inputNoStandard input (stdin) to provide to the program
compilerYesCompiler identifier (e.g. 'python-3.14', 'gcc-15'). Use list_compilers to see all options.

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden and does a solid job: it discloses the sandboxed Docker execution model, the third-party API dependency, a 30-second wall-clock limit, and a 512MB RAM ceiling. It stops short of stating auth requirements, rate limits, or whether submitted code or artifacts are persisted, which are meaningful gaps for a remote execution tool.

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

Conciseness4/5

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

Four short sentences, front-loaded with the core action and environment, then constraints and return values. Sentence two partly restates sentence one, and the return-value sentence duplicates information already available in the output schema, so a small amount of the text does not earn its place.

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

Completeness4/5

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

For a three-parameter execution tool with an output schema and no annotations, the description supplies the operational constraints an agent actually needs (sandbox, timeout, memory ceiling). The remaining omission is the dependency on list_compilers for valid compiler IDs, which is covered in the schema rather than the prose.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents code, input, and compiler, including the example compiler IDs and the pointer to list_compilers. The description only echoes that stdin is optional and that a compiler must be specified, adding no syntax or format detail beyond the structured fields, so the baseline of 3 applies.

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?

The description names a specific verb and resource ('Execute code') and pins down the execution environment ('sandboxed Docker container via the OnlineCompiler.io API'), which no sibling could plausibly share. The only sibling, list_compilers, is a discovery helper, and the phrase 'the specified compiler' implicitly signals that a compiler identifier must be obtained first, so an agent can tell the two apart without opening a schema.

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

Usage Guidelines3/5

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

Usage is only implied: an agent infers 'use this when you need to run code,' but there is no explicit statement of when to prefer this tool, when not to use it, or that list_compilers should be called first to obtain a valid compiler identifier. The routing hint for the sibling lives in the schema's compiler parameter, not in the description.

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.

  1. 2 tool updates
    • First observedlist_compilers
    • First observedrun_code

Publisher details

Operator
MicroPyramid
Vendor relationship
First-party
Restrictions
Free API key required; 100,000 runs a month free

Related MCP Connectors

Related MCP Servers

  • A
    license
    Not graded
    quality
    F
    maintenance
    Execute code in 8 programming languages via gVisor-sandboxed Docker containers. Supports Python, JS, TS, Go, Java, C++, C, and Bash.
    2
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    Enables secure cloud-based execution of code across 14+ programming languages within a sandboxed environment. It supports file management, standard input/output handling, and automatic generation of visual artifacts like plots and charts.
    MIT
  • A
    license
    A
    quality
    B
    maintenance
    Enables AI assistants to run code in 24 programming languages on HackerEarth's sandboxed servers and read the printed output or errors, without installing local toolchains. It also lists supported languages with exact identifiers for use when submitting code.
    2
    MIT
Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources