# MongoDB

> Use this tool when you need to interact with MongoDB databases directly within AI assistant conversations, enabling querying, inserting, and managing data for workflows like data analysis or content management. It provides a bridge between AI agents and MongoDB collections through the Model Context Protocol, allowing for flexible deployment via Docker or Node.js. This tool is ideal for use cases requiring database operations without leaving the conversation interface.

Canonical page: https://skillsregistry.net/skills/rock913-mongodb  
JSON: https://api.skillsregistry.net/v1/skills/rock913-mongodb

## Description

MongoDB MCP provides a bridge between AI assistants and MongoDB databases, enabling direct interaction with MongoDB collections through the Model Context Protocol. Built by Alex Andrushevich, this TypeScript implementation allows for querying, inserting, updating, and managing MongoDB data without leaving the conversation interface. The server can be configured with a MongoDB connection URL and deployed either via Docker or as a Node.js application, making it flexible for different integration needs. This implementation is particularly valuable for workflows requiring database operations, data analysis, or content management directly within AI assistant conversations.

## Trust

- **Trust score (0–1):** 0.64
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-02

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/rock913-mongodb)
- **Repository:** <https://github.com/rock913/mongo-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": "rock913-mongodb"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/rock913-mongodb` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/rock913-mongodb/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