# Docs Vector MCP

> Use this tool when you need to semantically search GitHub repository documentation using natural language queries. It solves problems of information retrieval and knowledge discovery by providing relevant documentation snippets through a standard MCP interface. The tool takes natural language queries as input and returns relevant documentation snippets as output, making it ideal for use cases where AI agents require specific information from large repositories.

Canonical page: https://skillsregistry.net/skills/meteorgeminy-docs-vector-mcp  
JSON: https://api.skillsregistry.net/v1/skills/meteorgeminy-docs-vector-mcp

## Description

Enables AI agents to semantically search GitHub repository documentation by automatically fetching, vectorizing, and indexing content into an Upstash Vector database. It provides a standard MCP interface for agents to retrieve relevant documentation snippets through natural language queries.

## Trust

- **Trust score (0–1):** 0.88
- **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/s199hkm71o)
- **Repository:** <https://github.com/MeteorGeminy/docs-vector-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": "meteorgeminy-docs-vector-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/meteorgeminy-docs-vector-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/meteorgeminy-docs-vector-mcp/pull`

---
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