eDiscovery Decoder News/Calc

安装

选择你使用的 AI 应用，然后复制设置。

通过 2/3 项检查 · 你的提问会经过开发者的服务器（mcp.ediscoverydecoder.com） · ✓ 命令已检查 2026年11月13日

claude mcp add --transport http --scope user ediscoverydecoder https://mcp.ediscoverydecoder.com/mcp

{
  "mcpServers": {
    "ediscoverydecoder": {
      "url": "https://mcp.ediscoverydecoder.com/mcp"
    }
  }
}

{
  "servers": {
    "ediscoverydecoder": {
      "type": "http",
      "url": "https://mcp.ediscoverydecoder.com/mcp"
    }
  }
}

哪些应用可以使用它

依据这个服务器的连接方式和各应用自己的文档，检查于 2026年11月10日。

通过互联网连接，适用于

ClaudeChatGPTGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatOpen WebUIRaycast

全部应用及其优缺点 →

它能做什么

工具名称和描述与服务器在 2026年11月15日 报告的完全一致。这些内容由作者撰写，不是我们写的；我们以纯文本形式显示。

• ping

  Health check: confirm the eDiscovery Decoder News/Calc MCP server is reachable before a demo or when troubleshooting a connection. Returns server name and version. No inputs.

• list_capabilities

  List the full eDiscovery Decoder MCP surface — every tool, prompt, and resource, plus the suggested demo flow and safety boundaries — with an example prompt for each. Call this first when you are unsure which tool fits the user's question, or when tool-search shows only a partial

• get_demo_guide

  Return a short, human-readable walkthrough for testing this server: the endpoint, the tool/prompt/resource names, and ready-to-paste sample prompts. Use to give someone a guided demo. For the full machine-readable capability catalog, use list_capabilities instead.

• get_resource_content

  Fetch the JSON behind a supported edd:// resource — the demo guide, TAR learning path, glossary, or news (latest / brief / by-date). Use when you want resource content but the client cannot read MCP resources directly, e.g. to pull glossary definitions or the news brief as a norm

• get_prompt_template

  Return the rendered text of one of this server's guided prompts (mcp-demo-tour, tar-matter-kickoff, weekly-digest). Use when the client can call tools but cannot open MCP prompts directly, or when you want to inspect a prompt's wording before using it.

• search_news

  Find recent eDiscovery / legal-AI / TAR news by topic, tag, or date range. Use when the user asks what's new or recent in eDiscovery, wants stories on a subject, or asks about a time window. For a ready-made top-stories roundup instead, use get_news_brief.

• get_news_brief

  Get the current eDiscovery Decoder news brief: top stories plus a Week in Review breakdown, returned both as structured data and as display-ready Markdown (formatted_brief) with a 'why it matters' line per story. Use when the user wants a roundup or summary of current eDiscovery

• calculate_review_metrics

  Score a coded sample when you have a full confusion matrix (true/false positives and negatives) — e.g. comparing a TAR model's calls against a reviewer's. Returns recall, precision, F1, accuracy, and in-sample elusion. Use calculate_control_set_recall if you only have relevant-fo

• calculate_elusion

  Estimate how much responsive/relevant material may remain in a set you chose NOT to review (the discard, null, or 'elusion' set). Use when a random sample of that excluded set has been coded — e.g. 'we sampled 400 culled docs and found 2 relevant.' Returns the elusion rate and a

• calculate_sample_size

  Work out how many documents to randomly sample to estimate a proportion (e.g. richness or elusion) at a target confidence level and margin of error, with finite-population correction. Use when planning a sample before review — 'how big a sample do we need?' Aggregate inputs only;

• calculate_tar_recall_estimate

  Estimate overall TAR recall and how many responsive docs were missed, by combining the responsive count already found with an elusion sample of the excluded set. Use when the user wants a recall % for the whole workflow, not just the elusion rate. For only the elusion rate and it

• calculate_prevalence_richness

  Estimate how rich or prevalent a population is — the share that is responsive/relevant/positive — from positive hits in a random sample, with a Wilson confidence interval. Use for 'what % of this set is relevant?' or to size review scope and cost expectations. Aggregate counts on

• calculate_control_set_recall

  Calculate recall against a known control set: the share of documents already confirmed relevant that the workflow found, with a Wilson confidence interval. Use when you have relevant-found and relevant-missed counts from a fixed reference set. For recall from a confusion matrix u

• compare_tar_cutoffs

  Compare candidate TAR score or rank cutoffs side by side: for each cutoff, how many docs sit above it, its share of the scored set, and (if responsive counts are given) an estimated precision. Use when deciding where to draw the review/cull line. Aggregate counts only; not legal

• validate_sample_design

  QC a TAR validation sampling plan: check whether it has the documented elements needed for a defensibility discussion (population, sample size, confidence level, sampling frame/method, randomization, etc.) and flag what is missing or inconsistent. Use to sanity-check a sampling p

基础检查i

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15日

• ! 注意

  作者与仓库一致

  注册中心没有列出源代码仓库，因此无法将发布者（ediscoverydecoder.com）与代码对应起来

• … 尚未检查

  仍在维护

  我们还没有从 GitHub 读取这个仓库

• … 尚未检查

  有许可证

  我们还没有从 GitHub 读取这个仓库

• ✓ 通过

  端点有响应

  在 683 毫秒内响应（HTTP 200）

• – 不适用

  使用 OAuth 登录

  无需登录

• ✓ 通过

  工具描述中没有隐藏指令

  已读取 15 个工具描述，未发现针对 AI 的隐藏指令

我们检查什么 → · JSON

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与“搜索与 AI 记忆”中的其他服务器比较i

• 星标数多于此分类中其他 6175 个服务器的 0%
• 发布到注册中心的时间比此分类中其他 6175 个服务器的 17% 更新
• 基础检查结果等于或优于此分类中其他 6175 个服务器的 50%

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。

功能相近的其他选择

同一分类、其他作者、命令已通过检查。官方的排在前面，再按星标排序。

如何看卡片：↓ 每周下载量i★ 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

OpenSEO

Keyword research, site audits, rank tracking and AI visibility for your AI agent.

作者：every-app·广泛使用·★ 2.8万·昨天更新

在云端运行✓ everyapp.com

接入方法

Exa

Connect AI agents to Exa for web search, content fetching, and multi-step research.

作者：exa-labs·广泛使用·★ 5234·2个月前更新

在云端运行✓ 服务方 · exa.aiPopNx 团队已实际试用

接入方法

Mockserver

Mock, record/replay, verify and chaos-test any HTTP, REST, gRPC or LLM dependency over MCP.

作者：mock-server·正在增长·★ 5011·19天前更新

在你的电脑上运行✓ 服务方 · mock-server.com

安装

Microsoft Learn MCP

Official Microsoft Learn MCP Server – real-time, trusted docs & code samples for AI and LLMs.

作者：MicrosoftDocs·广泛使用·★ 1992·12个月前更新

在云端运行✓ 服务方 · microsoft.comPopNx 团队已实际试用

接入方法

Docs

Search and read Empryo's documentation. Read-only, no auth, no local access.

作者：proxysoul·正在增长·★ 1614·2个月前更新

在云端运行✓ empryo.com

接入方法

• OpenSEO — 在云端运行，无需安装 · 不需要密钥
• Exa — 在云端运行，无需安装 · 不需要密钥 · 在 Claude 的目录中
• Mockserver — 需要安装在电脑上 · 不需要密钥
• Microsoft Learn MCP — 在云端运行，无需安装 · 不需要密钥 · 在 Claude 的目录中
• Docs — 在云端运行，无需安装 · 不需要密钥

作者的 README

仓库中没有找到 README