# Materials Project

> Use this tool when you need to access a vast database of material properties for computational materials science applications, such as materials discovery, property prediction, and crystallographic analysis. It provides core functionalities like searching materials by chemical elements, retrieving detailed properties by ID, and finding materials by chemical formula, returning structured data on formation energies, band gaps, and more. Ideal for researchers and AI assistants requiring programmatic access to extensive material properties data.

Canonical page: https://skillsregistry.net/skills/fair2wise-materials-project  
JSON: https://api.skillsregistry.net/v1/skills/fair2wise-materials-project

## Description

This Materials Project MCP server provides access to the Materials Project database through three core tools: searching for materials by chemical elements, retrieving detailed material properties by ID, and finding materials by chemical formula. Built using FastMCP and the mp-api library, it returns structured data including formation energies, band gaps, crystal systems, space groups, density, and stability information for computational materials science applications. The implementation is valuable for researchers and AI assistants working with materials discovery, property prediction, and crystallographic analysis where programmatic access to the Materials Project's extensive database of calculated material properties is needed.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/fair2wise-materials-project)
- **Repository:** <https://github.com/fair2wise/materials_project_mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "fair2wise-materials-project"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/fair2wise-materials-project` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/fair2wise-materials-project/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt