mat-db-mp
Query Materials Project database for crystal structures, computed properties, elastic/magnetic data, and structurally similar materials using the MP API.
Skill by learningmatter-mit
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
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About
Use cases: backend, data
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Python package
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/mat-db-mp
What's inside
- Skill name
mat-db-mp- Description
- Query Materials Project database for crystal structures, computed properties, elastic/magnetic data, and structurally similar materials using the MP API.
- License
- MIT
- Instructions
- 297 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Files (23)
- SKILL.md
- README.md · examples/
- elasticity_query.sh · examples/elasticity/
- high_bulk_modulus.json · examples/elasticity/
- si_elasticity.json · examples/elasticity/
- mp-1143.cif · examples/get_structure/
- mp-149.cif · examples/get_structure/
- mp-149_Si.cif · examples/get_structure/
- mp-19017.cif · examples/get_structure/
- structure_retrieval.sh · examples/get_structure/
- fe2o3_magnetism.json · examples/magnetism/
- ferromagnetic_materials.json · examples/magnetism/
- magnetism_query.sh · examples/magnetism/
- li_s_stability.sh · examples/query_mp/
- li_s_stable.json · examples/query_mp/
- similar_si_carbon_only.json · examples/similarity/
- similar_to_si.json · examples/similarity/
- similarity_search.sh · examples/similarity/
- find_similar_structures.py · scripts/
- get_elasticity.py · scripts/
- get_magnetism.py · scripts/
- get_structure_by_id.py · scripts/
- query_mp.py · scripts/
SKILL.md (first lines)
# Materials Project Database Query
<!-- mcp-tools-note -->
> [!NOTE]
> Steps written `server.tool` are MCP tool calls: `base.search_materials_project_by_formula` is the `search_materials_project_by_formula`
> tool of the `base` server (`mcp__base__search_materials_project_by_formula`, or
> `mcp__plugin_atomistic-skills_base__search_materials_project_by_formula` when installed as a plugin).
> Without a connected server, run the same tools from the shell. Tools named in
> one command share a process, so a model loaded by `load_model` stays loaded:
>
> ```bash
> ${CLAUDE_SKILL_DIR}/../../venv/run cpu python -m src.mcp_server.cli base search_materials_project_by_formula key=value search_materials_project_by_chemsys key=value
> ```
## Goal
To retrieve crystal structures and computed properties from the Materials Project database, enabling efficient materials discovery and property analysis. This skill provides access to:
- Basic material properties (energy above hull, formation energy, band gap)
- Elastic properties (bulk modulus, shear modulus, elastic tensors)
- Magnetic properties (magnetic ordering, magnetization, site moments)
- Structure similarity search (CrystalNN-based fingerprinting)
**Note**: For quick structure retrieval by formula or chemical system, MCP tools are also available (see [MCP Tools](#mcp-tools-for-quick-retrieval) section).
## Instructions
### 1. Query Materials by Chemical System or Formula
Use `query_mp.py` to search for materials by chemical system, formula, or elements with property filtering.
**Basic Query (Summary Endpoint)**:
```bash
${CLAUDE_SKILL_DIR}/../../venv/run cpu python ${CLAUDE_SKILL_DIR}/scripts/query_mp.py \
--chemsys "Li-S" \
--properties energy_above_hull formation_energy_per_atom band_gap \
--e_above_hull_max 0.05 \
--limit 10 \
--endpoint summary \
--output stable_li_s_materials.json
```
**Detailed Thermodynamic Data (Thermo Endpoint)**:
```bash
${CLAUDE_SKILL_DIR}/../../venv/run cpu python ${CLAUDE_SKILL_DIR}/scripts/query_mp.py \
--chemsys "Li-O" \
--endpoint thermo \
--limit 20 \
--output li_o_thermo.json
```
**Key Parameters**:
- `--chemsys`: Chemical system (e.g., "Li-S", "Si-O")
- `--formula`: Specific chemical formula (e.g., "LiFePO4")
- `--elements`: List of elements that must be present
- `--properties`: Properties to retrieve (default: energy_above_hull, formation_energy_per_atom)
- `--e_above_hull_max`: Maximum energy above hull for stability filtering (eV/atom)
- `--endpoint`: Choose `summary` (includes structures) or `thermo` (detailed thermodynamics, no structures)
- `--limit`: Maximum number of results to retrieve
**Output**: JSON file containing material IDs, formulas, CIF strings (summary endpoint), and requested properties.
### 2. Query Elastic Properties
Use `get_elasticity.py` to retrieve bulk modulus, shear modulus, and elastic tensor data.
**Query Specific Material**:
```bash
${CLAUDE_SKILL_DIR}/../../venv/run cpu python ${CLAUDE_SKILL_DIR}/scripts/get_elasticity.py \
--material_id mp-149 \
--output si_elasticity.json
```
**Filter by Bulk Modulus Range**:
```bash
${CLAUDE_SKILL_DIR}/../../venv/run cpu python ${CLAUDE_SKILL_DIR}/scripts/get_elasticity.py \
--bulk_modulus_min 200 \
--bulk_modulus_max 400 \
--output high_bulk_modulus.json
```
**Key Parameters**:
- `--material_id`: Specific MP ID(s) to query
- `--bulk_modulus_min/max`: Bulk modulus (VRH) range in GPa
- `--shear_modulus_min/max`: Shear modulus (VRH) range in GPa
**Output**: JSON file with bulk modulus, shear modulus (Voigt, Reuss, VRH averages), and full elastic tensor.
### 3. Query Magnetic Properties
Use `get_magnetism.py` to retrieve magnetic ordering, magnetization, and site-specific magnetic moments.
**Query Specific Material**:
```bash
${CLAUDE_SKILL_DIR}/../../venv/run cpu python ${CLAUDE_SKILL_DIR}/scripts/get_magnetism.py \
--material_id mp-19770 \
--output fe2o3_magnetism.json
```
**Filter by Magnetic Ordering and Magnetization**:
```bash
${CLAUDE_SKILL_DIR}/../../venv/run cpu python ${CLAUDE_SKILL_DIR}/scripts/get_magnetism.py \
--ordering FM \
--total_magnetization_min 10.0 \
--output ferromagnetic_materials.json
```
**Key Parameters**:
- `--material_id`: Specific MP ID(s) to query
- `--ordering`: Magnetic ordering type (FM, AFM, FiM, NM)
- `--total_magnetization_min/max`: Total magnetization range in μB
**Output**: JSON file with magnetic ordering, total magnetization, and per-site magnetic moments.
### 4. Retrieve Structures by Material ID
Use `get_structure_by_id.py` to retrieve crystal structures directly by their Materials Project ID.
**Single Structure Retrieval**:
```bashFrom learningmatter-mit/AtomisticSkills, MIT.
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Signals
- Stars
- 183
- Forks
- 31
- Open issues
- 0
- Last commit (this folder)
- Oct 5, 2026 (26 days ago)
- Last release
- Oct 6, 2026 (25 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Website
- arxiv.org/abs/2605.24002
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Build a solvated, charge-neutralized protein-ligand complex for OpenMM molecular dynamics simulation.
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mat-db-mp skill. Agent Mart. https://agentmart.dev/skills/learningmatter-mit-mat-db-mp (last updated 2026-10-24)