Click on "Deploy 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., "@JSON Suppressor Clean this JSON against the expected schema: {"name":"Alice","age":30,"extraField":"bad"}"
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.
A standalone MCP server that validates and cleans structured data returned by AI agents. It removes invented fields, coerces incorrect types, and ensures the output matches the expected schema before it enters your pipeline.
This repository contains the full implementation and runs independently. It does not depend on the full suite.
Add this server to your MCP client configuration (Claude Desktop, Cursor, Windsurf, or any MCP‑compatible environment):
{
"mcpServers": {
"json_suppressor": {
"command": "python3",
"args": ["/path/to/mcp-json-suppressor/server.py"]
}
}
}
Related MCP server: task-orchestrator
- Validates JSON against a schema
- Removes hallucinated or extra fields
- Coerces simple type errors where possible
- Returns cleaned JSON plus a list of violations
This suppressor is also included in the consolidated mcp-hallucination-suite, which bundles all four suppressors and provides a meta-orchestrator: https://github.com/steveswain14/mcp-hallucination-suite
mcp-prompt-suppressor
mcp-tool-response-suppressor
mcp-grounding-enforcer
This server cannot be deployed
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