EduAtlas
Live school vacancies from schools' own careers pages, and official school records. Free, no login.
作者提供的说明(英文原文)
Screenplay, film and story toolkit over MCP: PDF formatting, stats, diagnosis, video prompts.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
Authorization标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
这个地址需要在请求的 header 中放入密钥,而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。
在终端中运行这条命令
claude mcp add --transport http screenplay-formatter https://mcp.narracore.app/mcp --header 'Authorization: your-value'运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"screenplay-formatter": {
"url": "https://mcp.narracore.app/mcp",
"headers": {
"Authorization": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"screenplay-formatter": {
"type": "http",
"url": "https://mcp.narracore.app/mcp",
"headers": {
"Authorization": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个地址需要在请求的 header 中放入密钥,而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。
你的选择通过 Cookie 保存在这台设备上,无需账户。
Authorization 机密 HTTP header这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月8日
注册名称已通过域名 narracore.cn 验证(注册中心会核实域名所有权)
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
尚未检查;我们会轮流检查各个端点
尚未检查;我们会轮流检查各个端点
尚未检查;我们会在检查端点时读取工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
你需要填写:Authorization
它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。
GitHub 仓库最后更新于–,最新版本(1.4.0)于2个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。
同一分类中有:EduAtlas, RSS.com MCP by usefulapi, Castos MCP by usefulapi
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Live school vacancies from schools' own careers pages, and official school records. Free, no login.
Read podcasts and episodes; create and edit episodes, chapters and transcripts in RSS.com.
Read podcasts and episodes; create and update episodes; manage private subscribers in Castos.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
Turn rough screenplay text into professionally structured screenplay format and a print-ready PDF — from any MCP-compatible AI.
Remote MCP server (Streamable HTTP): https://mcp.narracore.app/mcp
Works with Claude, ChatGPT, Cursor, Gemini and any MCP-compatible client. Paste a rough script, get back structured blocks (scenes, characters, parentheticals, dialogue, transitions), layout diagnostics, and a typeset PDF identical to narracore.cn — fixed typewriter grid, embedded Sarasa Mono / Courier Prime fonts, Chinese and English (or mixed) tracks.
Beyond formatting, the same endpoint carries a film-breakdown protocol and a story-continuity protocol for AI agents (14 tools in total — see below).
https://mcp.narracore.app/mcp → Connect.Step-by-step: docs/install-claude.md
https://mcp.narracore.app/mcp.Step-by-step: docs/install-chatgpt.md
Settings → MCP → Add new global MCP server, type url:
{ "url": "https://mcp.narracore.app/mcp" }
Step-by-step: docs/install-cursor.md
Gemini CLI / Code Assist — add to settings.json:
{
"mcpServers": { "narracore-screenplay-formatter": { "httpUrl": "https://mcp.narracore.app/mcp" } } }
Step-by-step: docs/install-gemini.md
Fourteen tools over one endpoint, in three billing units (see Paid credits).
| Tool | What it does |
|---|---|
format_screenplay | Parse rough text (or typed blocks) → structured blocks → layout diagnostics → print-ready PDF (free validate_only mode included) |
analyze_screenplay | Deterministic stats: scene list with parsed headings, character table, dialogue ratio, action density |
diagnose_scenes | Scene shootability diagnosis — the calling AI cites evidence, the server validates and scores 0-100 (material mode free) |
convert_fountain | Blocks ↔ Fountain (plain-text screenplay interchange format), both directions |
build_video_prompts | Screenplay → structured video-prompt scaffolds: ~15s segments, ≤4 shots each, character registry, dialogue pre-filled verbatim, style guidance (checklist / editable presets / your own note) |
check_video_prompts | Free deterministic checks of finished video prompts against the screenplay: dialogue-verbatim lock, cut-point handoff, shared-content rules (violations) + eyeline/rhetoric/conflict advisories |
One credit covers one screenplay for 24 hours across all of the above (they share a content fingerprint — send the same script, or the blocks you got back, to several tools and it charges once).
Your agent watches the footage locally with its own vision model; this server supplies the protocol, the deterministic validation and the compilation.
| Tool | What it does |
|---|---|
get_film_contract | Free — the Film Contract by section: pipeline and entities, the long-take window protocol, observability levels, closed vocabularies + alias table, observation and reasoning prompt templates, reference ffmpeg recipes |
plan_film_analysis | Free — cut timestamps → the analysis topology every Film Protocol agent shares: numbered base shots, long-take windows, ≤20s / ≤8-shot analysis units |
validate_film_breakdown | Free preflight — schema, closed vocabularies, cross-references, window topology, provenance shape; returns a lossless normalized_patch and retry feedback for your model |
compile_film_breakdown | Billed: 1 credit per film analysis — authoritative validation → long-take merge (a 96s take is ONE shot in every statistic) → exact aggregates → labelled deterministic heuristics → PDF report with a 24h signed link |
For AI agents carrying a long-running story (novel, interactive fiction, tabletop campaign, worldbuilding) across context windows. The full text and the returned StoryState stay with you; the server stores nothing.
| Tool | What it does |
|---|---|
prepare_story_window | Free — split a conversation (verbatim user/assistant turns) into stable, hash-anchored units bound to your current state |
absorb_story_window | Billed: 1 credit per story project / 24h — validate and apply YOUR extraction: selectors must quote exact unit text, and the returned canon_patch is tail-hash-verified before you apply it |
render_story_handoff | Free — render the state you supply into a model-independent zh/en handoff document for a successor writer/AI |
| Tool | What it does |
|---|---|
check_credits | Show remaining credits for a license key, plus recent usage and the purchase link |
Structured input (typed blocks), diagnostics codes, and header-based auth are documented in the tool descriptions themselves — your AI already knows how to use them.
The free daily credit works with no key. To buy more:
NRC-XXXX-XXXX-XXXX-XXXX.Authorization: Bearer NRC-… in your client). Top-ups land on the same key.What one credit covers (three independent units — a credit spent on one is not a credit in another):
| Unit | Charged once per | Tools |
|---|---|---|
| Screenplay | one screenplay, for 24 hours | format_screenplay, analyze_screenplay, diagnose_scenes, convert_fountain, build_video_prompts |
| Film analysis | one analysis_id, for 24 hours | compile_film_breakdown |
| Story project | one story project, for 24 hours | absorb_story_window |
Free tier: one credit per day per visitor, any of the three. Failures are never charged; retrying the same request_id never double-charges.
Details: docs/pricing.md · Refund within 7 days if unused.
Your text is used only to produce your result. PDFs are deleted after 24 hours. License keys are stored hashed. Videos are never uploaded for film breakdowns. No training, no accounts, no newsletters. → docs/privacy.md
cn.narracore/screenplay-formatterThis repository is the public anchor for the hosted service — it contains documentation, examples, and registry metadata only. Docs are licensed CC-BY-4.0.