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Glama

Oqmd

by io.github.pipeworx-io

Search Materials

search_materials
Read-onlyIdempotent

Search the Open Quantum Materials Database for DFT-computed inorganic materials by composition and/or constituent elements, with optional band-gap and thermodynamic-stability filters. Returns formation energy (eV/atom), energy above the convex hull (stability), band gap, space group, and prototype. Keyless. Provide at least composition or element_set.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results, default 10, max 25.
compositionNoExact composition, e.g. "Fe2O3", "LiCoO2". Matched as an exact stoichiometry.
element_setNoConstituent elements the material must contain. Use OQMD set syntax: "(Al-O)" = contains Al or O; "(Fe-O),Ni" = (Fe or O) and Ni. A plain comma list like "Fe,O" is also accepted.
band_gap_minNoMinimum band gap in eV (exclusive). e.g. 0.5 to find semiconductors/insulators.
max_stabilityNoMaximum energy above the convex hull in eV/atom (exclusive). 0 = exactly on the hull (thermodynamically stable / ground state). e.g. 0.05 keeps near-stable phases.

Schema Changelog

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

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "composition": "Fe2O3"
+  },
+  {
+    "band_gap_min": 0.5,
+    "element_set": "(Fe-O)",
+    "limit": 15,
+    "max_stability": 0.05
+  }
+]
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds valuable context by listing specific returned fields (formation energy, hull distance, band gap, space group, prototype), clarifying keyless access, and specifying the input constraint. No contradiction.

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?

Three tight sentences: purpose, return fields, and key constraint. No filler, front-loaded with the most important information.

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?

For a search tool with no output schema, the description covers what is returned, how to filter, and input requirements. Minor gaps like sort order or default limits are not critical since limit is in the schema.

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

Parameters4/5

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

Schema coverage is 100% and each parameter is well described. The description adds the decisive 'at least one of composition or element_set' rule and explains the meaning of the stability filter in terms of convex hull distance, which enriches the schema's flat descriptions.

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 uses a specific verb 'Search' with an explicit resource (Open Quantum Materials Database) and identifies query dimensions (composition, elements) and filters. This clearly distinguishes it from siblings like get_material (likely retrieving by ID) and stable_phases.

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?

States a clear prerequisite: 'Provide at least composition or element_set', and notes keyless access. It doesn't explicitly name alternative tools, but the usage context is clear from the description.

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

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TDQS

A3.8/5.0
Disambiguation2/5

Many tools overlap in purpose: ask_pipeworx, ask_pipeworx_grounded, and deep_research all answer questions; multiple prediction market tools (polymarket_edges, polymarket_arbitrage, polymarket_edge_tracker, polymarket_fill_risk) have subtle distinctions. An agent would struggle to choose correctly among these.

Naming Consistency4/5

Tool names follow a consistent snake_case verb_noun pattern (e.g., list_subscriptions, generate_llms_txt). A few are noun phrases (stable_phases) but the style is uniform and predictable.

Tool Count2/5

33 tools is high for a single server, especially given the mix of two unrelated domains (materials database and general data querying). Many prediction market tools could be consolidated, and the broad scope suggests over-engineering.

Completeness3/5

The materials data side covers search and retrieval adequately. The query side offers many capabilities but has redundant paths (e.g., multiple ways to ask questions) and gaps in editing or updating data. Overall coverage is mixed.

Resources