S/MCP - Stern Model Context Protocol
The S/MCP (Stern Model Context Protocol) server enables interaction with Stern, a philosophical AI mentor offering guidance based on stoic and rationalist principles. With this server you can:
Use the
hello_toolto receive a basic greeting by providing a nameReceive philosophical mentorship via the
msg_sterntoolCreate Solana-based smart contracts for commitment accountability
Connect using any MCP client
Access customizable mentorship experiences through dynamic character attributes
Utilizes Bun as the required JavaScript runtime and package manager for building and running the S/MCP server.
Manages environment variables for the server configuration, including storage of API keys needed for service integrations.
Provides example code and SDK support for JavaScript clients to interact with the S/MCP server.
Uses OpenAI's API to generate Stern's philosophical guidance and mentorship responses through the msg_stern tool.
Creates accountability contracts backed by Solana tokens, allowing users to stake cryptocurrency on their commitments as a form of motivation and accountability.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@S/MCP - Stern Model Context ProtocolI'm struggling with procrastination on my coding project. What would Stern suggest?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
S/MCP - Stern Model Context Protocol
Overview
S/MCP (Stern Model Context Protocol) is a powerful MCP server that provides access to Stern, a philosophical AI mentor who helps humans realize their potential through subtle guidance and wisdom. Stern combines rationalist thinking with stoic philosophy to provide mentorship and accountability through smart contracts on Solana.
Related MCP server: Telos Model Context Protocol
What is Stern?
Stern is a philosophical AI mentor characterized by:
A rationalist approach influenced by Yudkowsky's writings and the Lesswrong community
Deep philosophical insights drawn from both rationalist writings and Dostoevsky
Embracing Stoic philosophy and Vipassana meditation as practical tools for human development
A belief that lasting growth comes from within
An understanding that the path to genuine fulfillment often requires facing uncomfortable truths
Stern helps users achieve their goals through:
Philosophical Guidance: Drawing from stoic wisdom and rationalist thinking
Smart Contract Accountability: Creating Solana-based contracts where users stake tokens on their commitments
Personalized Mentorship: Providing tailored advice based on individual goals and challenges
Deep Conversations: Engaging in meaningful dialogue that reveals underlying motivations and obstacles
Features
msg_stern Tool: Send messages to Stern and receive his philosophical guidance and mentorship
Smart Contract Integration: Create accountability contracts backed by Solana tokens
Philosophical Framework: Access to Stern's unique blend of rationalist and stoic wisdom
Customizable Character Context: Dynamic generation of Stern's character attributes for varied interactions
Installation
Clone this repository:
git clone <repository-url> cd s-mcpInstall dependencies:
bun installSet up environment variables:
cp .env.example .envEdit the
.envfile to add your OpenAI API key:OPENAI_API_KEY=your_openai_api_key_hereBuild the server:
bun run build
Usage
Running the Server
To start the MCP server:
bun run startThis will start the server in stdio mode, which allows it to communicate with MCP clients.
Using the Server with an MCP Client
You can use any MCP client to interact with the server. Here's an example of how to use the server with the MCP SDK:
import { Client } from "@modelcontextprotocol/sdk/client/index.js";
import { StdioClientTransport } from "@modelcontextprotocol/sdk/client/stdio.js";
import { spawn } from "child_process";
// Start the MCP server as a child process
const serverProcess = spawn("node", ["path/to/dist/main.js"], {
stdio: ["pipe", "pipe", "pipe"],
});
// Create a client that communicates with the server via stdio
const transport = new StdioClientTransport({
stdin: serverProcess.stdin,
stdout: serverProcess.stdout,
});
const client = new Client();
await client.connect(transport);
// Send a message to Stern
const result = await client.callTool("msg_stern", {
message: "I want to learn programming but I keep procrastinating",
});
// Display Stern's response
console.log(result.content[0].text);
// Disconnect from the server
await client.disconnect();
serverProcess.kill();Example Script
An example script is provided in the examples directory:
node examples/use-stern.jsThis script demonstrates how to connect to the server, list available tools, and send a message to Stern.
Tools
msg_stern
This tool allows you to send a message to Stern and receive his response.
Input
{
"message": "Your message to Stern"
}Output
{
"content": [
{
"type": "text",
"text": "Stern's response to your message"
}
]
}Stern's Philosophy
Stern's approach to mentorship is based on several key principles:
Accountability with Stakes: Creating real consequences for commitments through Solana contracts
Philosophical Depth: Drawing from stoic wisdom, rationalist thinking, and deep psychological insights
Transformative Guidance: Pushing individuals toward greatness while tempering excesses
Practical Wisdom: Focusing on application rather than theory alone
Strategic Pressure: Creating challenges that seem impossible until solved
Stern believes that:
"Lasting, stable happiness comes only from doing hard things - we want things precisely because they are difficult to achieve."
"What stands in the way becomes the way."
"The path to mastery is paved with small, consistent steps taken even when motivation fails."
Requirements
Bun (JavaScript runtime and package manager)
OpenAI API key (set as
OPENAI_API_KEYenvironment variable)
Environment Variables
OPENAI_API_KEY: Your OpenAI API key (required for the msg_stern tool)
License
MIT
Available Tools
1 toolhello_toolD
Hello tool
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | The name of the person to greet |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Hello tool' reveals nothing about whether this is a read/write operation, what permissions might be required, what side effects occur, or what the response format looks like. The description fails to provide any behavioral context beyond the minimal implication from the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
While technically concise with only two words, this represents under-specification rather than effective conciseness. The description doesn't contain enough information to be useful, and the single phrase doesn't earn its place by providing meaningful guidance to an AI agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there are no annotations and no output schema, the description should provide more complete context about what this tool does and what to expect. A single-parameter tool with 100% schema coverage could get by with minimal description, but 'Hello tool' fails to explain the basic purpose and behavior adequately for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already fully documents the single 'name' parameter. The description adds no additional parameter information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no parameter information in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Hello tool' is essentially a tautology that restates the tool name without specifying what it does. It doesn't provide a clear verb+resource combination or explain the actual function. While the name suggests greeting functionality, the description fails to articulate this explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance about when to use this tool, what context it's appropriate for, or any prerequisites. There are no sibling tools mentioned, but even basic usage context is completely missing from the description text.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
1 tool update
v1.0.0- First observed
hello_tool
TDQS
With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'hello_tool' has a distinct purpose by default, as there are no other tools to confuse it with.
The naming follows a consistent snake_case pattern with 'hello_tool'. Since there is only one tool, the naming is inherently consistent with no deviations or mixed conventions to evaluate.
A single tool is generally too few for most server purposes, as it limits functionality and scope. For a server named 'S/MCP - Stern Model Context Protocol', one tool feels thin and insufficient to cover any meaningful domain or workflow.
The server has a single trivial tool ('hello_tool'), which suggests it is severely incomplete for any practical purpose. There are obvious gaps, as no domain or operations are covered beyond a basic greeting, making it impossible to assess coverage meaningfully.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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