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Glama
tetracoralla

math-anchor

by tetracoralla

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
MATH_ANCHOR_PYTHONNoOptional. Set only when selecting a specific Python interpreter (Python 3.11 or newer).
MATH_ANCHOR_SDKROOTNoOptional. Explicit override for the SDK root used by Swift scripts.

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
math.runA

Use for exact or reliability-sensitive mathematics, especially fixed-width overflow and bits, IEEE-754, named rounding or division conventions, large integers, matrices, units and dimensions, uncertainty, probability, numerical methods, or finance. Do not use for trivial low-risk arithmetic. Always pass operation-specific fields inside the arguments object: {operation, arguments}; never flatten them. Known direct shapes need no describe call: integer.machine_arithmetic arguments include action, left, right, bitWidth, signedness, inputMode, and overflowBehavior; combinatorics.count arguments use action, n, and k. The typed operation keeps exact and approximate results separate; one successful ordinary call is sufficient.

math.batchA

Run 1 to 32 independent operations in order with per-item limits.

math.searchA

Search operations only when the id is unknown; otherwise use math.run.

math.describeA

Get schema and argument examples only for one unfamiliar operation selected by math.search. Do not call this for known integer.machine_arithmetic or combinatorics.count shapes. Examples are arguments objects; nest one under math.run.arguments and pass its id as math.run.operation.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A4.3/5.0

Scored across 4 tools

Disambiguation5/5

Each tool has a clearly distinct role: run executes a single operation, search finds operation IDs, describe returns schemas, and batch executes multiple operations. There is no meaningful overlap between them.

Naming Consistency5/5

All tool names follow the same math.<verb> convention with lowercase identifiers. The names are short, predictable, and consistent with each other.

Tool Count5/5

Four tools is well-scoped for this server: a single execution tool covering many operations, plus search, describe, and batching support. Each tool earns its place without redundancy.

Completeness5/5

The surface covers the full workflow of discovering an operation, understanding its schema, executing it, and batching multiple operations. Since math operations are stateless, no update or delete lifecycle is needed.

Maintenance

ActivityActive
ResponsivenessNo issues