Node.js/TypeScript MCP server for Atlassian Confluence. Provides tools enabling AI systems (LLMs) to list/get spaces & pages (content
Nothing to run from here
eDiscovery Decoder News/Calc is installed from its publisher's own source and answers where it runs, so this marketplace is not in the path of a single call. There is no address here to send one to, and a panel that pretended otherwise would be showing you an answer we made up. Install it and call it from your own client — the Installation tab has the entry for each one.
15
tools declared
—
trust score
remote
at its publisher
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calls last 7d
What it does
Free educational MCP for read-only eDiscovery news and TAR/review calculators.
Quickstart
# 1 — add it to Claude Code
claude mcp add --scope user --transport http ediscovery-decoder-news-calc-mcp https://mcp.ediscoverydecoder.com/mcp
# 2 — ask your agent for something these tools do
# ping, list_capabilities, get_demo_guide and 12 more
eDiscovery Decoder News/Calc costs nothing on mcprush: there is no plan to choose here, no cap to set and nothing mcprush can bill you for.
Publishernot claimed
MEAll 1 server
mcp.ediscoverydecoder.com1 server
1 category
Collected from a public index. Nobody has claimed this account, so nothing here was written by its author — claim it if it is yours.
Installation
Where are you running it?
Every route below installs the same thing and ends at the same approval screen. Nothing here runs on your machine and nothing runs on ours: this server answers at its publisher’s own address, and what you install is the connection straight to it.
Claude Codedeclared by this listing
This is a public server: it answers at its publisher’s own address and this marketplace is not in the path. Claude Code registers it in one command; --scope user makes it available in every project. The transport below is http, as the publisher's own manifest declares it.
claude mcp add --scope user --transport http ediscovery-decoder-news-calc-mcp https://mcp.ediscoverydecoder.com/mcpReconnect, or start a new session, and the tools appear in the model’s tool list.
Free on mcprush, and it answers at its publisher’s own address: this marketplace is not in the path, so there is no key of ours to hold and no card to add.
What it writes
One config entry pointing straight at the publisher’s own address — this marketplace is not in the path, and nothing from this listing executes on your machine.
What you approve
15 tools, with what each one reads, writes and reaches shown before you agree — the same list on every route above. Read the tool surface.
Tool surface
What the model actually sees. Descriptions are diffed on every release — see version history.
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.
No parameter schema on file.
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.
No parameter schema on file.
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.
No parameter schema on file.
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.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| uri | string | yes | — |
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.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| prompt_name | string | yes | — |
| audience | string | no | — |
| matter_description | string | no | — |
| week_start | string | no | — |
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.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| query | string | no | — |
| tags | array | no | — |
| date_from | string | no | — |
| date_to | no | — | |
| limit | integer | no | — |
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 a keyword search.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| current_limit | integer | no | — |
| week_limit | integer | no | — |
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-missed; calculate_elusion for a discard/null-set sample. Aggregate counts only; not legal advice.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| true_positives | integer | yes | — |
| false_positives | integer | yes | — |
| false_negatives | integer | yes | — |
| true_negatives | integer | yes | — |
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 interval. For an overall recall % from the same sample, use calculate_tar_recall_estimate. Aggregate c
| Parameter | Type | Required | Notes |
|---|---|---|---|
| relevant_found_in_sample | integer | yes | — |
| sample_size | integer | yes | — |
| confidence_level | number | no | — |
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.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| population_size | integer | yes | — |
| confidence_level | number | no | — |
| margin_of_error | number | yes | — |
| estimated_prevalence | number | no | — |
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 calculate_elusion. Aggregate counts only; not legal advice.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| responsive_found | integer | yes | — |
| excluded_population_size | integer | yes | — |
| elusion_responsive_hits | integer | yes | — |
| elusion_sample_size | integer | yes | — |
| confidence_level | number | no | — |
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.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| positive_hits | integer | yes | — |
| sample_size | integer | yes | — |
| population_size | integer | no | — |
| confidence_level | number | no | — |
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_metrics; from a discard-set sample use calculate_tar_recall_estimate. Aggregate counts only; not leg
| Parameter | Type | Required | Notes |
|---|---|---|---|
| relevant_found | integer | yes | — |
| relevant_missed | integer | yes | — |
| confidence_level | number | no | — |
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.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| scored_document_count | integer | yes | — |
| cutoffs | array | yes | — |
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 relying on it. Reviews metadata only — not a legal sufficiency opinion.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| population_size | integer | yes | — |
| sample_size | integer | yes | — |
| confidence_level | number | no | — |
| margin_of_error | number | no | — |
| sampling_frame | string | no | — |
| sampling_method | string | no | — |
| random_seed | string | no | — |
| generated_at | string | no | — |
| excluded_population_size | integer | no | — |
Free
$0 forever
- Every tool — any call limit is its publisher’s, not ours
- No card, and mcprush charges nothing for it
- Runs at its publisher’s own address — this marketplace is not in the path
- Nothing to cap, because mcprush bills nothing
What counts against your monthly calls
| Tool | Unit | Calls used | Out of the allowance |
|---|
Nothing here is billable: mcprush charges nothing to install eDiscovery Decoder News/Calc or to call it, at any volume.
Call allowance · this installenforced at the gateway
Monthly allowance, in calls
—
—
Alert at 80% · then the tool returns a normal MCP error
Used this month: —
—Grade not published
No rule-by-rule report on file for this release
Two independent axes, because powerful and malicious are different questions. The grade is threat only. The capability level is blast radius, and it is never a penalty on the grade — it is priced as one subtract-only term in the score, where you can see it.
This listing is an address its publisher runs, and you connect to it directly — this marketplace is not in the path. The scanner reads packages and public source, and an address is neither. So there is no grade — not a withheld one, an unmeasured one.
Release history
This is an address its publisher runs: which release it serves is theirs to choose, so there is nothing here to pin. The history below is for reading; the current release on file is 0.1.0.
0.1.0
undated
latestNo release note was published with this version.
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no reviews yet
Who can review
One review per account, from a signed-in account that does not publish this listing. Nothing else is asked — you can say what you think before you install it. Publishers can reply once per review, and a review can be edited or deleted by whoever wrote it.
Sign in to write one
Any signed-in account that does not publish eDiscovery Decoder News/Calc can review it, once — before installing it or after. A review from an account that has installed it is marked as one.
No reviews yet
Nobody has reviewed this listing. The rating on the card is the mean of the reviews written here and nothing else, so there is no rating until somebody writes the first — which takes a signed-in account that does not publish it, and nothing else.