Nexent
Nexent is a zero-code platform for auto-generating production-grade AI agents using Harness Engineering principles — unified tools, skills, memory, and orchestration with built-in constraints, feedback loops, and control planes.
What is Nexent?
Nexent is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to nexent is a zero-code platform for auto-generating production-grade ai agents using harness engineering principles — unified tools, skills, memory, and orchestration with built-in constraints, feedbac...
Nexent is a zero-code platform for auto-generating production-grade AI agents using Harness Engineering principles — unified tools, skills, memory, and orchestration with built-in constraints, feedback loops, and control planes.
This server falls under the Coding Agents category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- Nexent is a zero-code platform for auto-generating productio
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx nexentConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use Nexent
Nexent is an open-source, zero-code platform for auto-generating production-grade AI agents using Harness Engineering principles, combining unified tools, persistent layered memory, skill management, and multi-agent orchestration in a single deployable system. It supports 20+ document formats for knowledge bases, integrates with OpenAI-compatible LLM providers, and ships an MCP Tool Ecosystem for extensibility. Platform and ML teams use Nexent to build, version, and govern AI agents without writing agent framework code, leveraging built-in RBAC, budget controls, and agent marketplace capabilities.
Prerequisites
- Docker 24+ and Docker Compose, or a Kubernetes 1.24+ cluster with Helm 3+
- Minimum 4 CPU cores and 8 GiB RAM (16 GiB recommended for production)
- x86_64 or ARM64 host architecture
- An OpenAI-compatible LLM API key (OpenAI, Azure OpenAI, or a compatible provider)
- An MCP-compatible client such as Claude Desktop for connecting to Nexent's MCP server
Clone the Nexent repository
Clone the repository to your local machine or deployment server. Both Docker and Kubernetes deployment options are available in the repo.
git clone https://github.com/ModelEngine-Group/nexent.gitDeploy with Docker (recommended for getting started)
Run the Docker deployment script from the docker subdirectory. The script will interactively prompt for deployment options and saves choices to deploy.options for reuse.
cd nexent/docker
bash deploy.shOr deploy on Kubernetes with Helm
For production Kubernetes deployments, use the Helm chart deployment script. Requires at least 16 GiB RAM and Kubernetes 1.24+.
cd nexent/k8s/helm
./deploy.shAccess the Nexent web UI
Once deployment completes, open the Nexent web interface to create agents, configure LLM providers, upload knowledge base documents, and set up MCP tool integrations. The default port is configured during deploy.sh.
Connect your MCP client to Nexent
Add Nexent as an MCP server in your Claude Desktop or other MCP client configuration. Nexent exposes its agent and tool capabilities through its MCP endpoint.
{
"mcpServers": {
"nexent": {
"command": "npx",
"args": ["nexent"]
}
}
}Create your first zero-code agent
In the Nexent UI, use natural language prompts to define an agent's goals, assign it tools from the MCP ecosystem, and configure memory and skill parameters. No code is required.
Nexent Examples
Client configuration
MCP client configuration for connecting to a locally deployed Nexent instance.
{
"mcpServers": {
"nexent": {
"command": "npx",
"args": ["nexent"]
}
}
}Prompts to try
Use Nexent's AI agent platform through your MCP-connected client.
- "Create a research agent that searches the web and summarizes findings into a report"
- "List all agents in my Nexent workspace and show their current status"
- "Upload this PDF to the knowledge base and make it available to the customer support agent"
- "Roll back the sales agent to version 2 from last week"Troubleshooting Nexent
deploy.sh fails with insufficient memory errors
Nexent requires at least 8 GiB RAM for Docker and 16 GiB for Kubernetes. Increase Docker Desktop memory allocation in Settings > Resources, or scale up your Kubernetes node pool.
LLM API calls from agents return authentication errors
In the Nexent web UI, verify that your OpenAI-compatible API key is correctly configured under the LLM Provider settings. Nexent uses OpenAI-compatible endpoints, so any compatible base URL and key should work.
MCP tools are not visible to agents after configuration
Navigate to the MCP Tool Ecosystem section in the Nexent UI and verify the tool connections are active. Restart the Nexent services with bash deploy.sh --components app if tool registration fails.
Frequently Asked Questions about Nexent
What is Nexent?
Nexent is a Model Context Protocol (MCP) server that nexent is a zero-code platform for auto-generating production-grade ai agents using harness engineering principles — unified tools, skills, memory, and orchestration with built-in constraints, feedback loops, and control planes. It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Nexent?
Follow the installation instructions on the Nexent GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with Nexent?
Nexent works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Nexent free to use?
Yes, Nexent is open source and available under the MIT license. You can use it freely in both personal and commercial projects.
Nexent Alternatives — Similar Coding Agents Servers
Looking for alternatives to Nexent? Here are other popular coding agents servers you can use with Claude, Cursor, and VS Code.
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Goose
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Antigravity Awesome Skills
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★ 24.5kA coding agent toolkit that provides IDE-like semantic code retrieval and editing tools, enabling LLMs to efficiently navigate and modify codebases using symbol-level operations instead of basic file reading and string replacements.
Browse More Coding Agents MCP Servers
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Set Up Nexent in Your Editor
Choose your AI client for step-by-step setup instructions.
Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
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