# MongoDB MCP Server for LLMs

> Use this tool when you need to interact with MongoDB databases using natural language, enabling large language models (LLMs) to query collections, inspect schemas, and manage data. It solves problems related to data access and management by providing a Model Context Protocol (MCP) server interface that takes in natural language inputs and returns relevant data outputs. This tool is ideal for use cases where LLMs require direct database interaction, such as data-driven conversational applications or knowledge graph construction.

Canonical page: https://skillsregistry.net/skills/nickiiitu-mongodb-model-context-protocol-mcp  
JSON: https://api.skillsregistry.net/v1/skills/nickiiitu-mongodb-model-context-protocol-mcp

## Description

A Model Context Protocol server that enables LLMs to interact directly with MongoDB databases, allowing users to query collections, inspect schemas, and manage data through natural language.

## Trust

- **Trust score (0–1):** 0.90
- **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/vuxqqmbr2q)
- **Repository:** <https://github.com/nickiiitu/MongoDB-Model-Context-Protocol-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": "nickiiitu-mongodb-model-context-protocol-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/nickiiitu-mongodb-model-context-protocol-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/nickiiitu-mongodb-model-context-protocol-mcp/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