MCP server

ExtensionDash

io.github.tonic20/extensions-dashboard

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

Research extension listings and search results; track installs, keyword rankings, and competitors.

Working at last checkAbout 6,198 tokens per request once connected14 tools

Website

https://extensiondash.com/mcp

At a glance

Type: MCP server
Publisher: Not verified
Status: Working at last check
Tools: 14
Token cost: About 6,198 tokens per request
Sets up in: Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok
Last checked: 26 Oct 2026, 08:29 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 extensions-dashboard https://extensiondash.com/mcp

Claude Desktop

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

Codex (config.toml)

[mcp_servers.extensions-dashboard]
url = "https://extensiondash.com/mcp"

Gemini CLI

{"mcpServers":{"extensions-dashboard":{"httpUrl":"https://extensiondash.com/mcp"}}}

Cursor

{"mcpServers":{"extensions-dashboard":{"url":"https://extensiondash.com/mcp"}}}

VS Code

{"servers":{"extensions-dashboard":{"type":"http","url":"https://extensiondash.com/mcp"}}}

Antigravity

agy mcp add extensions-dashboard https://extensiondash.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":"extensions-dashboard","server_url":"https://extensiondash.com/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"extensions-dashboard","server_url":"https://extensiondash.com/mcp"}

Tools

add_competitor ~444 tokens
Start tracking a competitor for an extension. Takes the store and id of a search_catalog row (as external_id), so a listing you just found can be promoted without looking anything up in between. Promoting a listing is what earns it a store fetch: its description, install count, rating and language
add_keyword ~506 tokens
Start tracking a search term for an extension. The term is added once per store the extension is listed in, and a rank fetch is enqueued for each store that was not already tracking it. The position is not available when this returns. Call list_keywords with the same extension_id until this term's
get_extension ~317 tokens
One extension in full: every store listing's latest numbers plus its tracked keywords and their current positions. Each listing's rank is its position by users within its store, computed from the current user count; ties share a rank (rank_tied = others at the same count); rank_change is the move s
get_keyword_ranks ~521 tokens
Daily search position history for an extension's tracked keywords, one series per term per store. Every point carries the depth it was scanned to, because a position only means something against the size of the pool it came from: #1 of 9 and #1 of 50 are different results. A null position means we
get_keyword_serp ~394 tokens
The search page for one of an extension's tracked keywords, as this account last recorded it — who was on it, in what order, and which way each of them moved over the past week. Read from recorded history, not from the store: no fetch, no waiting, no egress spent. Use this when you want movement, o
get_listing ~366 tokens
One extension's full listing from the catalog -- any extension, tracked by this account or not: description, users, rating, reviews, version, languages, categories, permissions and publisher. Pass the store and id of a search_catalog row as store and external_id. rank is the position by users within
get_metrics_history ~639 tokens
Daily-or-sparser history of an extension's numbers: user count, rating and ratings count, each as a map of ISO date to value. "listings" is this extension's own store listings; "competitors" is its roster from list_competitors. store and days filter both. A map holds only dates actually observed; a
list_competitors ~352 tokens
Who this extension competes with, measured across every keyword it tracks. Two sets. "competitors" is the roster you promoted with add_competitor: their descriptions, install counts and ratings are recorded, and their positions are kept even on days they fall out of the results. "candidates" — retu
list_extensions ~180 tokens
Every extension this token's owner tracks, with each store listing's latest numbers: user count (and whether the store rounded it), the 7-day change, rating, ratings count and category rank. Start here when this connection has an account: every tracking tool takes an extension_id from this list. N
list_keywords ~675 tokens
Every search term tracked for one extension, one row per term per store. status is "pending" until a fetch has landed since the term was tracked, and "scanned" once one has. A "scanned" row with a null position means we searched depth_scanned results and this extension was not among them — that is
list_scrape_runs ~274 tokens
Recent scrape attempts against your own extensions, newest first, with their outcome and any error. Covers both the listing fetches and the rank fetches for the search terms they track. Use this after add_keyword to watch the rank fetch: the run is targeted at the search term, and a failed fetch ap
remove_competitor ~254 tokens
Stop tracking a competitor for an extension. Stops the store fetches. The recorded history is kept, so adding the same competitor again later restores its charts rather than starting from zero — and its positions carry on being observed either way, because they come from searches this account alrea
remove_keyword ~378 tokens
Stop tracking a search term for an extension, across every store it was tracked in. Positions already recorded are kept; only the tracking stops. Other extensions tracking the same term are unaffected, including ones that track the same store listing: every extension's keywords are its own. A term
search_catalog ~898 tokens
Search one store's catalog of extensions fetched so far, for market and niche research: store "chrome" (default) or "firefox", one per call -- Chrome users are a rounded weekly count, Firefox's an exact daily average, so the two are never mixed. listed and known in each answer show how much of that

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