About systemprompt-agent-server
systemprompt-agent-server is an MCP server for creating and managing AI agents through system prompts and tools. It integrates with systemprompt.io and supports prompt versioning, resources, sampling, and notifications.
Key features
- 01Create and edit AI agents
- 02Manage versioned system prompts
- 03Create and browse agent resources
- 04Sampling and event notifications
Use cases
- 01Configuring agents with custom prompts and tools
- 02Maintaining prompt versions and metadata
- 03Providing agent resources to MCP clients
MCP support
Exposes agent, prompt, resource, and system-management tools to MCP clients. Sampling and notifications require clients that support those features; it is designed to work with multimodal-mcp-client.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEsystemprompt-agent-server
Website | Documentation | Blog | Get API Key
A specialized Model Context Protocol (MCP) server that enables you to create, manage, and extend AI agents through a powerful prompt and tool management system. This server integrates with systemprompt.io to provide seamless creation, management, and versioning of system prompts through MCP.
An API KEY is required to use this server. This is currently free, although this may change in the future. You can get one here.
This server uses Sampling and Notification functionality from the @modelcontextprotocol/sdk. This will only work with advanced clients that support these features. A free opensource client multimodal-mcp-client can be used to provide a complete voice-powered AI workflow solution.
Required Client
This server is designed to work with the multimodal-mcp-client - a voice-powered MCP client that provides the frontend interface. Please make sure to set up both components for the full functionality.
Why Use This Server?
- Agent Management: Create and manage AI agents with customized system prompts and tool configurations
- Extensible Tool System: Add, modify, and combine tools to enhance your agents' capabilities through MCP
- Prompt Management: Centralized management of system prompts with versioning and metadata support
- Type-Safe Integration: Full TypeScript support with proper error handling
- MCP Compatibility: Works seamlessly with multimodal-mcp-client and other MCP-compatible clients
- Open Source: Free to use and modify under the MIT license
Features
Core Functionality
- MCP Protocol Integration: Full implementation of Model Context Protocol for seamless AI agent interactions
- Voice-Powered Interface: Compatible with voice commands through multimodal-mcp-client
- Real-Time Processing: Supports streaming responses and real-time interactions
- Type-Safe Implementation: Full TypeScript support with proper error handling
Agent Management
- Create and configure AI agents with specific capabilities
- Manage agent states and contexts
- Define agent behaviors through system prompts
- Monitor and debug agent interactions
- Version control for agent configurations
- Resource management for agent assets
Advanced Tools System
Built-in tools include:
- Prompt Management
create_prompt- Create new system prompts with metadataedit_prompt- Update existing system prompts with versioningget_prompt- Retrieve specific prompt configurations
- Resource Management
create_resource- Create new agent resources and configurationsedit_resource- Modify existing agent resourceslist_resources- Browse available agent resourcesread_resource- Access specific agent resource content
- System Tools
systemprompt_heartbeat- Monitor system status and healthsystemprompt_fetch_resources- Retrieve all available resources
- Agent Management
create_agent- Create new systemprompt agentsedit_agent- Modify existing systemprompt agentslist_agents- View available systemprompt agents
Sampling & Notifications
- Advanced sampling capabilities for AI responses
- Real-time notification system for agent events
- Configurable sampling parameters
- Event-driven architecture for notifications
Integration Features
- API Key management and authentication
- User status and billing information tracking
- Subscription management
- Usage monitoring and analytics
Development Tools
- Built-in debugging capabilities
- Test utilities and fixtures
- Type-safe mocking utilities
- Comprehensive testing framework
🎥 Demo & Showcase
Watch our video demonstration to see Systemprompt MCP Client in action:
The demo showcases:
- Voice-controlled AI interactions
- Multimodal input processing
- Tool execution and workflow automation
- Real-time voice synthesis
Development
Install dependencies:
npm install
Build the server:
npm run build
For development with auto-rebuild:
npm run watch
Installation
Installing via Smithery
To install SystemPrompt Agent for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install systemprompt-agent-server --client claude
Manual Installation
To manually configure with Claude Desktop, add the server config:
On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"systemprompt-agent-server": {
"command": "/path/to/systemprompt-agent-server/build/index.js"
}
}
}
Debugging
Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector, which is available as a package script:
npm run inspector
The Inspector will provide a URL to access debugging tools in your browser.
Testing
This project uses Jest for testing with TypeScript and ESM (ECMAScript Modules) support.
Test Configuration
The test setup includes:
- Full TypeScript support with ESM modules
- Global fetch mocking
- Automatic test reset between runs
- Custom matchers for validation
- Type-safe mocking utilities
Module Resolution
The project uses a dual module resolution strategy:
- Source code uses ESM (ECMAScript Modules) with
.jsextensions - Tests use CommonJS for compatibility with Jest
This is configured through two TypeScript configurations:
tsconfig.json: Main configuration for source code (ESM)tsconfig.test.json: Test-specific configuration (CommonJS)
// Source code imports (ESM)
import { Something } from "../path/to/module.js";
// Test file imports (CommonJS)
import { Something } from "../path/to/module";
Running Tests
# Run tests
npm test
# Watch mode
npm run test:watch
# Coverage report
npm run test:coverage
Test Structure
Tests are located in __tests__ directories next to the files they test. The naming convention is *.test.ts.
Related Links
- Multimodal MCP Client - Voice-powered MCP client
- systemprompt.io Documentation
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.