Tool Output Truncator and Size Limiter Connector for AI agents.
3 live capabilities
Prevent context window overflows with safe UTF-8 text truncation
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Why people use Tool Output Truncator and Size Limiter
Prevent context window crashes with capability Output Truncator and Size Limiter
With this MCP, that manual guesswork disappears. You can precisely measure and shrink any output so it fits perfectly within your agent's limits. You get clean, usable data every time without the risk of broken characters.
What Vinkius changes
You get clean, manageable data that won't crash your agent's memory.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 6,100+ Connectors
- Real-world use case 01
Analyzing massive log files
An engineer needs to analyze a 50MB log file.
- Real-world use case 02
Web scraping data processing
A developer scrapes a webpage with heavy emoji use.
- Real-world use case 03
Database export summaries
A data analyst pulls a large SQL export.
Complete set · 3capabilities
The complete Tool Output Truncator and Size Limiter capability set.
These are the exact actions your AI can choose when you ask it to work with Tool Output Truncator and Size Limiter.
01—03
3 capabilities in this set.
Part of 3 available through Tool Output Truncator and Size Limiter.
- 01 Capability
Calculate exact byte size
Calculates the exact UTF-8 byte size of a string. Use this to check if your data will fit in the context window.
- 02 Capability
Truncate capability output
Safely shrinks a string to fit a byte limit. It prevents character corruption by respecting multi-byte symbols.
- 03 Capability
Validate truncation integrity
Validates that a truncated string is still valid. It ensures no characters were broken during the shrinking process.
Set up in minutes
One URL. Then ask Tool Output Truncator and Size Limiter to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Tool Output Truncator and Size Limiter from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_UEkFfAH48DMhTjp9teljwRif7CSSMVf1wSx6W85D/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it Tool Output Truncator and Size Limiter, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Tool Output Truncator and Size Limiter for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_UEkFfAH48DMhTjp9teljwRif7CSSMVf1wSx6W85D/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the Tool Output Truncator and Size Limiter URL.
- Step 03
Save and start
Save the connection and enable Tool Output Truncator and Size Limiter in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"tool-output-truncator-and-size-limiter": {
"url": "https://edge.vinkius.com/vk_preview_UEkFfAH48DMhTjp9teljwRif7CSSMVf1wSx6W85D/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using Tool Output Truncator and Size Limiter
Open Agent mode in chat and ask: "Using Tool Output Truncator and Size Limiter, help me...". 3 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"tool-output-truncator-and-size-limiter": {
"url": "https://edge.vinkius.com/vk_preview_UEkFfAH48DMhTjp9teljwRif7CSSMVf1wSx6W85D/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using Tool Output Truncator and Size Limiter
Ask Copilot: "Using Tool Output Truncator and Size Limiter, help me...". 3 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"tool-output-truncator-and-size-limiter": {
"url": "https://edge.vinkius.com/vk_preview_UEkFfAH48DMhTjp9teljwRif7CSSMVf1wSx6W85D/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using Tool Output Truncator and Size Limiter
Open Cascade and ask: "Using Tool Output Truncator and Size Limiter, help me...". 3 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"tool-output-truncator-and-size-limiter": {
"url": "https://edge.vinkius.com/vk_preview_UEkFfAH48DMhTjp9teljwRif7CSSMVf1wSx6W85D/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using Tool Output Truncator and Size Limiter
Ask Cline: "Using Tool Output Truncator and Size Limiter, help me...". 3 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add tool-output-truncator-and-size-limiter --transport http "https://edge.vinkius.com/vk_preview_UEkFfAH48DMhTjp9teljwRif7CSSMVf1wSx6W85D/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using Tool Output Truncator and Size Limiter
Ask Claude: "Using Tool Output Truncator and Size Limiter, show me...". 3 tools are ready
Where the request belongs
Work Tool Output Truncator can move forward.
Developers and data analysts who build agents that interact with large files, web scrapers, or massive database exports.
AI Engineer
Managing context window limits when building complex agentic workflows.
Data Scientist
Feeding large datasets or long log files into an agent for analysis.
Automation Developer
Ensuring web scraping outputs don't break the LLM during automated processing.
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Bring your own AI
Change the model, client or framework. Keep Tool Output Truncator connected.
-
Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
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Before you connect
Questions about Tool Output Truncator.
The practical details behind the request, access and result.
How does the Capability Output Truncator and Size Limiter prevent errors?
It prevents errors by ensuring that large data outputs are resized to fit within the specific byte limits of your agent's context window, preventing crashes and lost information.
Will the Capability Output Truncator and Size Limiter break my emojis?
No. Unlike standard text cutting, this MCP is designed to respect UTF-8 encoding, meaning it won't slice through multi-byte characters like emojis or special symbols.
Can I use the Capability Output Truncator and Size Limiter with any AI client?
Yes, as long as your client is MCP-compatible, such as Claude, Cursor, or Windsurf, you can use this to manage your data.
How do I know if the Capability Output Truncator and Size Limiter worked correctly?
You can use the built-in validation capability to confirm that the truncated text is still structurally sound and hasn't lost any character integrity.
Is the Capability Output Truncator and Size Limiter useful for web scraping?
Absolutely. It's perfect for scraping large amounts of web data where you need to trim the content to a specific size before your agent processes it.
How does this prevent character corruption?
The truncate_tool_output capability identifies the exact byte boundaries of UTF-8 characters. If a truncation would split a multi-byte character, the capability backtracks to the start of that character sequence, ensuring the resulting string remains valid.
Why use byte size instead of character count?
LLM context windows are limited by tokens and bytes, not just character counts. Since a single character can occupy multiple bytes in UTF-8, using calculate_exact_byte_size provides the most accurate way to manage the actual data footprint.
Can I verify if a truncation was successful?
Yes, you can use the validate_truncation_integrity capability to check if the processed content respects the byte limit and maintains character integrity.
One connection away
Give your agent a direct line to Tool Output Truncator.
Connect Tool Output Truncator once. Keep it beside 6,100+ managed Connectors when the next task needs more.
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