Software engineering is evolving into agentic engineering. According to the Stack Overflow Developer Survey 2025, 84% of respondents use or plan to use AI tools in their development, up from 76% the previous year. At this rate, the tooling needs to keep pace.
Last year, we introduced the MongoDB MCP Server to give agents the connectivity they need to interact with MongoDB, helping them generate context-aware code. But connectivity was only the start. Agents are generalists by design, and they don't inherently know the best practices and design patterns that real-world production systems demand.
Today, we're addressing this by introducing official MongoDB Agent Skills: structured instructions, best practices, and resources that agents can discover and apply to generate more reliable code across the full development lifecycle, from schema design and performance optimization to implementing advanced capabilities like AI retrieval.
To bring this directly into the tools you use, we're also launching plugins for Claude Code, Cursor, Gemini CLI, and VS Code, combining the MongoDB MCP Server and Agent Skills in a single, ready-to-use package.
Turning coding agents into MongoDB experts
Coding agents are great at producing working code, but they still make common mistakes in production systems, often defaulting to relational thinking that doesn't translate well to MongoDB, such as:
Over-normalizing schemas, ignoring MongoDB's document-oriented strengths.
Underusing compound indexes, causing performance bottlenecks at scale.
Misusing indexes and search indexes, overlooking the consistency trade-off for high-performance full-text search.
Because these pitfalls mirror common human errors, they are naturally reflected in agent outputs. MongoDB Agent Skills address this by providing expert guidance to agents, like schema design heuristics, indexing strategies, query patterns, and operational safeguards, enabling agents to ship more reliable, more consistent code faster.
Agent Skills were introduced by Anthropic as an open standard and have since been adopted by the leading AI development tools, including Claude Code, Cursor, Codex, and more.
This initial release covers the full application development lifecycle on MongoDB, from connection management and schema design to guidance on implementing advanced capabilities. We will continue to update and expand our skills library based on user needs.
Figure 1. MongoDB Agent Skills.
Scaling agentic engineering with MongoDB
As organizations embrace agentic software engineering, existing processes and workflows must be reimagined. The MongoDB MCP Server and MongoDB Agent Skills are built for this shift and work best together, giving builders and agents the tools to move fast without sacrificing guardrails or control.
The MongoDB MCP Server serves as the connectivity layer for your MongoDB deployments. It manages authentication and defines exactly what agents can access and do. Combined with MongoDB’s native authorization, it ensures agents operate with only the permissions they need, while giving teams governance through configurable controls like disabling specific tools.
Agent Skills ensure agents follow best practices from the start, reducing architectural risk, accelerating implementation, and raising the baseline quality of every agent-generated code.
While some skills can be used independently, others work in conjunction with the MongoDB MCP Server for workflows that require it. To simplify setup, the MCP Server and skills are now packaged together as plugins and extensions for Claude Code, Cursor, Gemini CLI, and VS Code, bringing these capabilities directly into your preferred tools.
Figure 2. MongoDB for Claude plugin in action.
We also encourage you to build your own skills as your agentic workflows mature. Whether enforcing internal naming conventions, custom data modeling patterns, or team-specific workflows, skills give you a practical way to codify institutional knowledge and ensure every agent and every developer works from the same playbook.
How to get started
Whether you’re using Claude Code, Cursor, Gemini CLI, or other AI development tools, you can install the MongoDB MCP Server and Agent Skills in seconds.
For example, in Claude Code, install the plugin that bundles both:
For Cursor, Gemini CLI, and VS Code extensions, refer to their respective documentation.
You can also install the skills for most coding agents using the Vercel Skills CLI (requires Node.js):
If you prefer, you can manually clone the GitHub repository and copy the skills into the appropriate folder for your agent.
Similarly, to install the MongoDB MCP Server, use the following command:
Agentic engineering is changing how teams work, and it is changing fast. Agents need the context and guidance to meet the standards of real-world production applications. With the official MongoDB Agent Skills and plugins, builders can move faster with confidence, and organizations can adopt coding agents knowing that MongoDB best practices are embedded directly into every workflow.
Next Steps
Ship faster, more reliable apps on MongoDB with Agent Skills. Install for Claude Code, Cursor, Gemini CLI and VS Code!
Facts Only
MongoDB Agent Skills: official set of instructions, best practices, and resources for coding agents
84% of respondents in Stack Overflow Developer Survey 2025 plan to use AI tools, up from 76% the previous year
Plugins available for Claude Code, Cursor, Gemini CLI, and VS Code
Executive Summary
The article discusses the evolution of software engineering towards agentic engineering, with a focus on the integration of AI tools for coding and development, particularly in the context of MongoDB databases. This change is reflected in the 84% of respondents in the Stack Overflow Developer Survey 2025 who plan to use AI tools, up from 76% the previous year.
To address the challenges posed by this shift, MongoDB has introduced official Agent Skills - structured instructions, best practices, and resources that agents can discover and apply to generate more reliable code across the full development lifecycle. These skills are now available as plugins for various tools such as Claude Code, Cursor, Gemini CLI, and VS Code.
The goal of these MongoDB Agent Skills is to turn coding agents into experts in working with MongoDB databases, helping them avoid common mistakes like over-normalizing schemas or underusing compound indexes. By providing expert guidance on schema design, indexing strategies, query patterns, and operational safeguards, the skills aim to improve the quality of agent-generated code.
Full Take
The article highlights the growing trend towards agentic engineering, where AI agents are increasingly used in software development. However, it also acknowledges that these agents still make common mistakes in production systems, often due to their lack of understanding of best practices and design patterns for real-world applications.
By introducing Agent Skills, MongoDB aims to bridge this gap by providing expert guidance to agents on schema design, indexing strategies, query patterns, and operational safeguards. This move reflects a broader effort in the AI development community to ensure that agents are equipped with the knowledge they need to generate reliable code that meets industry standards.
However, it is important to note that while Agent Skills can help improve the quality of agent-generated code, they do not entirely eliminate the need for human oversight and judgment in software development. As AI continues to evolve, it will be crucial to continue refining these tools and strategies to ensure that they serve as effective aids rather than replacements for human developers.
Sentinel — Human
The analysis suggests that this text is likely written by a human. While there are some signs of AI influence, the overall quality, passion, and unique characteristics indicate a high probability of human authorship.