readability-mcp-server
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.
README
readability-mcp-server
An MCP server that lets any AI agent check and improve the plain-language quality of its own text — before that text ever reaches a human. Fully local: no API key, no network call, no external service. It's a pure computation tool, so nothing you pass through it ever leaves the machine it's running on.
Unlike the other tools in this series (scamlens, clearread, clauselens), this one isn't a website a person opens — it's infrastructure for the AI agent ecosystem itself. Any MCP-compatible client (Claude Code, Claude Desktop, or any other) can call it directly.
Why
Agents generate a lot of text — replies, documentation, notices, error messages — and mostly have no way to check whether that text is actually easy for the recipient to read before sending it. This server gives any agent that self-check as a first-class tool call, using the same plain-language engine (sentence splitting + a vetted complex-to-plain word dictionary) already shipped and tested in clearread, the standalone web app in this series — here exposed for programmatic use instead of pasted by hand into a browser.
Tools
readability_score_text
Computes Flesch Reading Ease and Flesch-Kincaid Grade Level for a block of
English text. Returns supported: false with structural counts only for
non-Latin script, since the Flesch formulas assume English syllable
patterns.
readability_simplify_text
Rewrites text in plainer language — splits overly long sentences at natural
clause boundaries and substitutes common bureaucratic vocabulary for plainer
equivalents — and reports the Flesch Reading Ease score before and after, so
you can confirm the rewrite actually helped. English only, by design: word
substitution is unreliable across languages with richer morphology, so
non-Latin-script text is detected and passed through unchanged rather than
risk broken grammar (see the note in src/services/simplify.ts about why a
few tempting dictionary entries, like "accompanied" → "went with", were left
out after they broke common fixed phrases like "must be accompanied by").
Install and configure
Clone and build:
git clone https://github.com/wedo911/readability-mcp-server.git
cd readability-mcp-server
npm install
npm run build
Add it to your MCP client's config (e.g. claude_desktop_config.json, or a
project's .mcp.json for Claude Code):
{
"mcpServers": {
"readability": {
"command": "node",
"args": ["/absolute/path/to/readability-mcp-server/dist/index.js"]
}
}
}
Run the tests
npm run build
node --test tests/textStats.test.mjs tests/simplify.test.mjs
Try it without a client
The MCP Inspector can call tools directly from the command line:
npx @modelcontextprotocol/inspector --cli node dist/index.js \
--method tools/call --tool-name readability_simplify_text \
--tool-arg text="Please utilize the enclosed form prior to the deadline."
License
MIT — see LICENSE.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。