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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
runA

Execute Pylpex code and return the result.

Pylpex is a custom programming language. Before executing code:

  1. Check pylpex://documentation for syntax reference

  2. Review pylpex://examples for working patterns

  3. Ensure code follows Pylpex syntax conventions

Args: code: Valid Pylpex source code to execute

Returns: The evaluated result of the code execution

Example usage: run("2 + 2") # Returns: 4 run("function double(x) { return x * 2 } double(5)") # Returns: 10

tokenizeB

Convert Pylpex code into tokens for analysis.

Args: code: Valid Pylpex source code to tokenize

Returns: List of tokens with their types, values, and positions

get_variablesB

Get all variables in the current interpreter state.

resetB

Reset the interpreter state.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription
get_documentationPylpex language documentation and syntax guide
get_examplesCollection of working Pylpex code examples

TDQS

A3.7/5.0

Scored across 4 tools

Disambiguation5/5

Each tool has a clearly distinct purpose with no overlap: get_variables retrieves interpreter state, reset clears it, run executes code, and tokenize analyzes code structure. The descriptions make these roles unambiguous, preventing agent misselection.

Naming Consistency5/5

All tool names follow a consistent verb-based pattern (get_variables, reset, run, tokenize) without mixing conventions. The naming is straightforward and predictable, enhancing readability and agent usability.

Tool Count4/5

With 4 tools, the count is reasonable for a language interpreter server, covering core operations like execution, state management, and analysis. It could benefit from additional tools (e.g., for debugging or syntax validation) but is well-scoped for basic functionality.

Completeness4/5

The toolset covers essential interpreter workflows: running code, inspecting state, resetting state, and tokenizing code. Minor gaps exist, such as lack of tools for step-through debugging or syntax checking, but agents can work around these with the provided tools.

Maintenance

ActivityInactive
ResponsivenessNo issues