Slimcontext MCP Server

Name: Slimcontext MCP Server
Author: agentailor

by agentailorversion 0.1.2i★ –iRuns on your computer

Registry nameio.github.agentailor/slimcontext-mcp-server

Install

Overview

Description from the maker (original English)

MCP Server for SlimContext - AI chat history compression tools

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Chat & email

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "slimcontext": {
      "command": "npx",
      "args": [
        "-y",
        "slimcontext-mcp-server"
      ]
    }
  }
}

Run this in your terminal

claude mcp add slimcontext -- npx -y slimcontext-mcp-server

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "slimcontext": {
      "command": "npx",
      "args": [
        "-y",
        "slimcontext-mcp-server"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "slimcontext": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "slimcontext-mcp-server"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account agentailor, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Chat & emaili

More stars than 0% of the other 1769 servers in this category
Published to the registry more recently than 0% of the other 1769 servers in this category
Basic checks equal to or better than 100% of the other 1769 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Slimcontext MCP Server safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.2) reached the registry 14 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Vexa, emailmd, MCP WhatsApp Cloud

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

SlimContext MCP Server

A Model Context Protocol (MCP) server that wraps the SlimContext library, providing AI chat history compression tools for MCP-compatible clients.

Overview

SlimContext MCP Server exposes two powerful compression strategies as MCP tools:

`trim_messages` - Token-based compression that removes oldest messages when exceeding token thresholds
`summarize_messages` - AI-powered compression using OpenAI to create concise summaries

Installation

npm install -g slimcontext-mcp-server

or

pnpm add -g slimcontext-mcp-server

Development

# Clone and setup

git clone cd slimcontext-mcp-server pnpm install

Build

pnpm build

Run in development

pnpm dev

Type checking

pnpm typecheck

Configuration

MCP Client Setup

Add to your MCP client configuration:

"mcpServers": { "slimcontext": { "command": "npx", "args": ["-y", "slimcontext-mcp-server"] } } }

Environment Variables

OPENAI_API_KEY: OpenAI API key for summarization (optional, can be passed as tool parameter)

Tools

trim_messages

Compresses chat history using token-based trimming strategy.

Parameters:

messages (required): Array of chat messages
maxModelTokens (optional): Maximum model token context window (default: 8192)
thresholdPercent (optional): Percentage threshold to trigger compression 0-1 (default: 0.7)
minRecentMessages (optional): Minimum recent messages to preserve (default: 2)

Example:

"messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "Hello!" }, { "role": "assistant", "content": "Hi there! How can I help you today?" }, { "role": "user", "content": "Tell me about AI." } ], "maxModelTokens": 4000, "thresholdPercent": 0.8, "minRecentMessages": 2 }

Response:

"success": true, "original_message_count": 4, "compressed_message_count": 3, "messages_removed": 1, "compression_ratio": 0.75, "compressed_messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "assistant", "content": "Hi there! How can I help you today?" }, { "role": "user", "content": "Tell me about AI." } ] }

summarize_messages

Compresses chat history using AI-powered summarization strategy.

Parameters:

messages (required): Array of chat messages
maxModelTokens (optional): Maximum model token context window (default: 8192)
thresholdPercent (optional): Percentage threshold to trigger compression 0-1 (default: 0.7)
minRecentMessages (optional): Minimum recent messages to preserve (default: 4)
openaiApiKey (optional): OpenAI API key (can also use OPENAI_API_KEY env var)
openaiModel (optional): OpenAI model for summarization (default: 'gpt-4o-mini')
customPrompt (optional): Custom summarization prompt

Example:

"messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "I want to build a web scraper." }, { "role": "assistant", "content": "I can help you build a web scraper! What programming language would you prefer?" }, { "role": "user", "content": "Python please." }, { "role": "assistant", "content": "Great choice! For Python web scraping, I recommend using requests and BeautifulSoup..." }, { "role": "user", "content": "Can you show me a simple example?" } ], "maxModelTokens": 4000, "thresholdPercent": 0.6, "minRecentMessages": 2, "openaiModel": "gpt-4o-mini" }

Response:

"success": true, "original_message_count": 6, "compressed_message_count": 4, "messages_removed": 2, "summary_generated": true, "compression_ratio": 0.67, "compressed_messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "system", "content": "The user expressed interest in building a web scraper and requested help with Python. The assistant recommended using requests and BeautifulSoup libraries for Python web scraping." }, { "role": "assistant", "content": "Great choice! For Python web scraping, I recommend using requests and BeautifulSoup..." }, { "role": "user", "content": "Can you show me a simple example?" } ] }

Message Format

Both tools expect messages in SlimContext format:

interface SlimContextMessage {

role: 'system' | 'user' | 'assistant' | 'tool' | 'human'; content: string; }

Error Handling

All tools return structured error responses:

"success": false, "error": "Error message description", "error_type": "SlimContextError" | "OpenAIError" | "UnknownError" }

Common error scenarios:

Missing OpenAI API key for summarization
Invalid message format
OpenAI API rate limits or errors
Invalid parameter values

Token Estimation

SlimContext uses a simple heuristic for token estimation: Math.ceil(content.length / 4) + 2. This provides a reasonable approximation for most use cases. For more accurate token counting, you would need to implement a custom token estimator in your client application.

Compression Strategies

Trimming Strategy

Preserves all system messages
Preserves the most recent N messages
Removes oldest non-system messages until under token threshold
Fast and deterministic
No external API dependencies

Summarization Strategy

Preserves all system messages
Preserves the most recent N messages
Summarizes middle portion of conversation using AI
Creates contextually rich summaries
Requires OpenAI API access

License

MIT

Contributing

Fork the repository
Create a feature branch
Make your changes
Add tests for new functionality
Submit a pull request

SlimContext - The underlying compression library
Model Context Protocol - The protocol specification
MCP SDK - TypeScript SDK for MCP

Slimcontext MCP Server

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Chat & emaili

Common questions

Alternatives

Vexa

emailmd

MCP WhatsApp Cloud

README from the maker

SlimContext MCP Server

Overview

Installation

or

Development

Build

Run in development

Type checking

Configuration

MCP Client Setup

Environment Variables

Tools

trim_messages

summarize_messages

Message Format

Error Handling

Token Estimation

Compression Strategies

Trimming Strategy

Summarization Strategy

License

Contributing

Related