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matmcp

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Find likely matching materials from autogenerated robocrystallographer descriptions. Returns lists of matches; use fetch with a result id for detailed metadata.

Instructions

Define OpenAI compatible search.

Search through the autogenerated robocrystallographer descriptions of materials to return lists of likely matching materials.

Does not return the detailed metadata associated with a material. To retrieve this, use the fetch method for a given result id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultsNoA list of results

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It does disclose a meaningful behavioral trait beyond the schema: results are fuzzy ('likely matching') and deliberately omit `metadata`. However it says nothing about auth, rate limits, result caps, pagination, or ranking behavior, which are significant gaps for an unannotated search tool.

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

Conciseness3/5

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

The body is tight and front-loads the useful limitation-then-alternative pattern, but the opening sentence 'Define OpenAI compatible search' is a near-tautology of the title that consumes space without informing the agent. One sentence is waste out of four.

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

Completeness3/5

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

An output schema exists, so return values needn't be explained, and the description usefully covers the metadata omission and the fetch handoff. Against that, the sole parameter is undocumented and there are no annotations, leaving the agent without enough to know what a valid `query` looks like.

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

Parameters2/5

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

There is one parameter (`query`) at 0% schema description coverage, so the description must compensate. It only implies that the query is text matched against material descriptions; it never states whether the input is free text, a chemical formula, an element list, or a structured expression, nor any length or syntax constraints.

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

Purpose4/5

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

The description gives a clear verb+resource: search the autogenerated robocrystallographer descriptions of materials to return matching materials. It distinguishes itself from the sibling `fetch` by stating it returns lists of likely matches rather than detailed metadata. The leading sentence 'Define OpenAI compatible search' is confusing filler that doesn't add meaning.

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?

It explicitly routes the agent to the alternative: results lack `metadata`, and to get it you should use `fetch` for a given result `id`. That is a concrete when-to-use-this vs. when-to-use-sibling statement. It doesn't cover exclusions like when not to search at all, but the key routing guidance is present.

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