# BioBTree

> BioBTree — tamerh-biobtree. Use this tool when you need to integrate and query large amounts of biomedical data from multiple sources, solving problems such as data fragmentation and inconsistent identifiers. BioBTree provides a unified graph database with billions of cross-reference edges, taking in diverse data sources and outputting structured, authoritative information. It is ideal for use cases requiring reliable and up-to-date biomedical data, such as scientific research, clinical decision support, and AI model training.

Canonical page: https://skillsregistry.net/skills/tamerh-biobtree  
JSON: https://api.skillsregistry.net/v1/skills/tamerh-biobtree

## Description

A unified biomedical graph database that integrates 50+ primary data sources — genes, proteins, compounds, diseases, pathways, and clinical data — into a single queryable graph with billions of cross-reference edges. Its native MCP server gives LLMs direct access to structured, authoritative biomedical data, complementing their reasoning with reliable identifiers and up-to-date database content.

## Trust

- **Trust score (0–1):** 0.73
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/b6wioa50w1)
- **Repository:** <https://github.com/tamerh/biobtree>

## 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": "tamerh-biobtree"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/tamerh-biobtree` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/tamerh-biobtree/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