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kehvinbehvin/json-mcp-filter

by Various

JSON MCP server to filter only relevant data for your LLM

K

MCP

kehvinbehvin/json-mcp-filter

Added 1 June 2026

#claude-mcp #data #data-extraction #data-filtering #json #json-analysis #json-filter #json-mcp-server

Overview

An open source MCP server written in JavaScript that filters JSON data to extract only relevant fields for an LLM. It helps reduce token usage and noise by allowing developers to specify which parts of a JSON structure are passed to the language model.

Best for

Best for
Developers using MCP to optimize JSON data sent to LLMs, especially in prototyping or low‑traffic projects

Use cases

  • Stripping irrelevant keys from large JSON payloads before sending to an LLM
  • Reducing token consumption when feeding structured data into a context window
  • Enforcing a whitelist of fields for consistent LLM input across endpoints

Notes

An open source MCP server written in JavaScript that filters JSON data to extract only relevant fields for an LLM. It helps reduce token usage and noise by allowing developers to specify which parts of a JSON structure are passed to the language model.

24 stars on GitHub. Last updated 2026-03-30. Licensed MIT.

Use cases

  • Stripping irrelevant keys from large JSON payloads before sending to an LLM
  • Reducing token consumption when feeding structured data into a context window
  • Enforcing a whitelist of fields for consistent LLM input across endpoints

Pros

  • Lightweight and straightforward JavaScript implementation
  • Open source with a permissive license for modification
  • Targets a specific pain point in MCP workflows

Cons

  • Small community (24 stars) may mean limited support or slower updates
  • Requires familiarity with Model Context Protocol ecosystem
  • No built-in field validation or error handling beyond basic filtering

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Lightweight and straightforward JavaScript implementation
  • Open source with a permissive license for modification
  • Targets a specific pain point in MCP workflows

Cons

  • Small community (24 stars) may mean limited support or slower updates
  • Requires familiarity with Model Context Protocol ecosystem
  • No built-in field validation or error handling beyond basic filtering