Skip to main content
Glama

batch

Execute multiple bridge operations in one round trip, returning a result per call so a single failure does not abandon the rest.

Instructions

Run several bridge operations in ONE round trip and return a result per call.

A round trip costs a poll interval plus latency against single-digit ms of actual work, so a sequence of small calls is nearly all waiting. Each entry is a dict with an "op" key:

{"op": "world"} {"op": "find", "ref": ...} {"op": "get", "ref": ..., "name": ...} {"op": "set", "ref": ..., "name": ..., "value": ...} {"op": "call", "ref": ..., "function": ..., "args": [...]} {"op": "props", "ref": ..., "include_super": bool, "read_soft": bool, "pattern": str} {"op": "funcs", "ref": ...} {"op": "objects", "class_name": ..., "limit": int} {"op": "types", "pattern": ..., "limit": int} {"op": "console", "command": ...} {"op": "dump", "kind": ...}

Each result is {op, ok, result} or {op, ok: false, error}. One failing call does not abandon the rest, so a batch is safe to use for exploration.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
callsYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden of explaining behavior. It transparently documents the input format (each call has an 'op' key), the list of supported operations, the per-call response structure including error handling, and the fact that one failure does not abort the rest. It doesn't mention side effects of specific inner operations (like set), but the overall behavior is well conveyed.

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?

The description is slightly long due to the enumerated operation examples, but this length is justified because the schema is minimal. It is well-structured with a clear opening, a brief rationale, and then a formatted list of examples followed by the response format. The information is front-loaded with the main purpose stated first.

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?

Given the absence of an output schema and the minimal input schema, the description provides sufficient context for an agent to understand both the input and output formats. It explains the return contract (each result is {op, ok, result} or error) and covers error handling. It doesn't enumerate every possible operation, but the examples are representative and cover the common cases, making the tool usable.

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

Parameters5/5

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

The input schema only defines 'calls' as an array of objects with additionalProperties true, providing no structural detail. The description fills this gap completely by specifying that each object must contain an 'op' field and showing concrete examples for each supported operation. This is essential for correct usage and is done in a clear, actionable way.

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 clearly states the tool's core function: 'Run several bridge operations in ONE round trip.' It explicitly differentiates this from individual operations by emphasizing the batch nature and the efficiency gain, making it distinct from the sibling tools like get_property or call_function.

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?

The description provides practical guidance on when to use the batch tool by explaining the overhead of individual calls ('A round trip costs a poll plus latency...') and noting that it is safe for exploration due to partial failure. It could be more explicit in saying 'use this instead of calling each operation individually,' but the rationale is clear enough.

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

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/littleRabbit94/ue-bridge'

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