Skip to main content
Glama
jim-coyne

Hyperfabric MCP Server

fabricsGetFabricCandidates

Retrieve candidate configurations for a fabric, including options to filter by name, transaction ID, time range, and include reviews or activity events.

Instructions

Get the list of candidate configurations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fabricIdYesThe fabric id or name.
nameNoThe candidate configuration name.
txnIdNoThe transaction sequence number of the candidate configuration.
needInactiveNoInclude committed/reverted candidate configurations.
needReviewsNoInclude the list of reviews of the candidate configurations.
needEventsNoInclude the list of activity events of the candidate configurations.
startTimeNoStart value of the time range in [RFC3339](https://datatracker.ietf.org/doc/html/rfc3339#section-5.8) format (e.g. `YYYY-MM-DDTHH:MM:SSZ`).
endTimeNoEnd value of the time range in [RFC3339](https://datatracker.ietf.org/doc/html/rfc3339#section-5.8) format (e.g. `YYYY-MM-DDTHH:MM:SSZ`).
maxNoThe max number of candidates to return in the response.
cursorNoAn optional cursor for pagination.
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions 'list' which implies a read operation, but doesn't disclose behavioral traits like whether it's paginated (though 'cursor' parameter hints at this), rate limits, authentication needs, or what happens with invalid inputs. The description adds minimal context beyond the basic action.

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?

The description is a single, efficient sentence with zero waste—it directly states the tool's purpose without fluff. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.

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

Completeness2/5

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

Given the complexity (10 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what 'candidate configurations' are, how results are structured, or behavioral aspects like pagination or error handling. For a tool with rich parameters and no structured safety hints, this minimal description leaves significant gaps.

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 fully documents all 10 parameters. The description adds no meaning beyond what the schema provides—it doesn't explain relationships between parameters (e.g., how 'fabricId' filters results) or typical usage patterns. Baseline 3 is appropriate as the schema does the heavy lifting.

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

Purpose3/5

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

The description 'Get the list of candidate configurations' clearly states the action (get) and resource (candidate configurations), but it's vague about what 'candidate configurations' are in this context. It doesn't distinguish this tool from sibling tools like 'fabricsGetFabricCandidate' (singular) or 'fabricsGetAllFabrics', leaving the scope ambiguous.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. With many sibling tools available (e.g., 'fabricsGetFabricCandidate' for a single candidate, 'fabricsGetAllFabrics' for fabrics), there's no indication of context, prerequisites, or exclusions, leaving the agent to guess based on parameter names alone.

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/jim-coyne/hyperfabric_MCP'

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