"Optimizing and Improving Flutter Application Performance" matching MCP servers:

A local-first, open-source MCP server that analyzes jobs, matches your CV, tailors documents, and tracks applications — all on your machine with no data uploaded.

Enables exploring Steam store reviews and community discussion threads with server-side filtering, temporal analysis, and metadata context for understanding player sentiment and feedback beyond store page noise.

tooltrim reduces the tokens agents spend re-reading bloated tool results. Run it as an MCP server exposing compress and expand_tool_output, or as a gateway in front of any upstream MCP server: it re-exposes the upstream tools unchanged and shrinks each result (HTML/JSON/logs/tables) before it reaches the model, keeping the relevant content only.

Lets any AI agent score and simplify its own text before it reaches a human, using Flesch readability metrics and plain-language rewrites entirely on the local machine.

Provides MCP-compatible AI clients with offline text analysis and rewriting tools, including statistics, extractive summaries, keywords, readability scores, case conversion, entity extraction, and diffing, all running locally without API keys or network calls.

Unofficial MCP server for working with Kagi without API access (you'll need to be a customer, tho). Searches and summarizes. Uses Kagi session token for easy authentication.

Provides 14+ character-level text analysis tools that give LLMs the ability to accurately count letters, analyze individual characters, and work with text at the character level—overcoming tokenization limitations.

Precise character-level string indexing for LLMs. Provides tools for finding, extracting, and manipulating text by exact character position to solve position-based operations.

distill-mcp-v2 is a high-performance, network-dependency-free Python FastMCP server designed to aggressively optimize Large Language Model (LLM) context windows. It provides specialized tools for compressing and analyzing massive AI-agent payloads without losing critical semantic information.

Enables counting characters or bytes in text with options to include or exclude whitespace. Provides a simple tool for text analysis and length measurement.

A Node.js implementation of the Kagi Model Context Protocol server that enables Claude AI to search the web and summarize documents, videos, and audio using Kagi's APIs.

An MCP server for managing and persisting notes, offering CRUD operations, note summarization, and resource-based access via a note:// URI scheme.

Fetches and processes Hacker News discussions to prepare them for Claude to generate high-quality summaries, handling comment structure and metadata to help Claude understand the relative importance of different comments.

Provides intelligent transcript processing capabilities for Claude, featuring natural formatting, contextual repair, and smart summarization powered by Deep Thinking LLMs.

A simple TypeScript-based MCP server that implements a notes system, allowing users to create, list, and generate summaries of text notes via Claude.

This server provides a tool to generate unified diffs between two text strings, facilitating text comparison and analysis.

Counts characters and words in both Japanese and English text files, with special handling for Japanese morphological analysis and proper character counting excluding spaces and line breaks.

A TypeScript-based MCP server for handling a simple notes system with NextJS that supports creating and summarizing text notes using MCP concepts.

A simple note storage system that allows creating, storing, and summarizing notes with customizable detail levels.

This TypeScript-based MCP server allows users to manage and interact with a note system through Model Context Protocol, enabling note creation and summarization with URIs and metadata.