MCP server

eDiscovery Decoder News/Calc Official

com.ediscoverydecoder/mcp

Checked 25 Oct 2026, 20:29 UTC · Connected to it and listed its tools

Free educational MCP for read-only eDiscovery news and TAR/review calculators.

Working at last checkVerified publisher: ediscoverydecoder.comAbout 3,133 tokens per request once connected15 tools

Website

https://mcp.ediscoverydecoder.com/mcp

At a glance

Type: MCP server
Publisher: ediscoverydecoder.com (verified by the MCP Registry)
Status: Working at last check
Tools: 15
Token cost: About 3,133 tokens per request
Sets up in: Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok
Last checked: 25 Oct 2026, 20:29 UTC

Connect it to your agent

Add to Cursor Add to VS Code VS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

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

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.ediscoverydecoder]
url = "https://mcp.ediscoverydecoder.com/mcp"

Gemini CLI

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

Cursor

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

VS Code

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

Antigravity

agy mcp add ediscoverydecoder https://mcp.ediscoverydecoder.com/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"ediscoverydecoder","server_url":"https://mcp.ediscoverydecoder.com/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"ediscoverydecoder","server_url":"https://mcp.ediscoverydecoder.com/mcp"}

Tools

calculate_control_set_recall ~239 tokens
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 use calculate_review_
calculate_elusion ~247 tokens
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 Wilson confidence in
calculate_prevalence_richness ~224 tokens
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 only; not legal advice
calculate_review_metrics ~244 tokens
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-found vs relevant-miss
calculate_sample_size ~239 tokens
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; not legal advice.
calculate_tar_recall_estimate ~277 tokens
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 its interval, use calc
compare_tar_cutoffs ~254 tokens
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 advice.
get_demo_guide ~117 tokens
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_news_brief ~180 tokens
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 AI news rather than
get_prompt_template ~204 tokens
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.
get_resource_content ~189 tokens
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 normal tool result.
list_capabilities ~124 tokens
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 list.
ping ~88 tokens
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.
search_news ~201 tokens
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.
validate_sample_design ~306 tokens
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 protocol before relyi

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