Google Search Console integration for Model Context Protocol (MCP)
Nothing to run from here
Analook — Competitor Intelligence 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.
8
tools declared
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trust score
remote
at its publisher
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calls last 7d
What it does
Competitor intelligence for AI agents — SEO, traffic, social, Product Hunt, pricing, AI insights.
Quickstart
# 1 — add it to Claude Code
claude mcp add --scope user --transport http analook-competitor-intelligence-mcp https://www.analook.com/mcp/
# 2 — ask your agent for something these tools do
# analyze_competitor, get_report_status, get_report and 5 more
Analook — Competitor Intelligence costs nothing on mcprush: there is no plan to choose here, no cap to set and nothing mcprush can bill you for.
Publishernot claimed
G1All 1 server
Gingiris-10311 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 analook-competitor-intelligence-mcp https://www.analook.com/mcp/Reconnect, 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
8 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.
Submit a competitor analysis job. Analyzes a competitor's website across 15+ data sources (SEO, traffic, social, Product Hunt, GitHub, Wayback Machine history, AI-generated insights, etc.) and returns a job_id. Use get_report_status(job_id) to poll and get_report(job_id) to retrieve results when status='completed'. Typical analysis takes 2-5 minutes. Requires authentication (
| Parameter | Type | Required | Notes |
|---|---|---|---|
| url | string | yes | — |
| product_name | no | — | |
| lang | no | — | |
| context | string | yes | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, r |
| llm_model | string | yes | The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model |
| conversation_id | string | no | Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep |
Poll an analysis job's status. Args: job_id: ID returned from analyze_competitor() Returns: {status: 'running'|'completed'|'failed', progress?: str, report_url?: str}
| Parameter | Type | Required | Notes |
|---|---|---|---|
| job_id | string | yes | — |
| context | string | yes | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, r |
| llm_model | string | yes | The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model |
| conversation_id | string | no | Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep |
Fetch the full competitor analysis report as structured JSON. Reports contain: website snapshot, Wayback Machine history, SEO/traffic data (DataForSEO), social media presence, Product Hunt launches, GitHub stats, pricing, funding, AI-generated business insights, growth playbooks, and more. Args: job_id: ID from analyze_competitor(); status must be 'completed' Ret
| Parameter | Type | Required | Notes |
|---|---|---|---|
| job_id | string | yes | — |
| context | string | yes | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, r |
| llm_model | string | yes | The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model |
| conversation_id | string | no | Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep |
Fetch the competitor analysis report as human-readable Markdown. Suitable for piping into agents that prefer text over structured JSON, or for direct display to end users. Args: job_id: ID from analyze_competitor(); status must be 'completed' Returns: {markdown: str} or {error: str}
| Parameter | Type | Required | Notes |
|---|---|---|---|
| job_id | string | yes | — |
| context | string | yes | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, r |
| llm_model | string | yes | The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model |
| conversation_id | string | no | Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep |
List your recent competitor analysis reports (up to 50). Requires authentication. Returns a lightweight list (id, url, product_name, created_at, status) — use get_report(job_id) to fetch the full report for any of them. Returns: {reports: [{id, url, product_name, created_at, status}, ...]}
| Parameter | Type | Required | Notes |
|---|---|---|---|
| context | string | yes | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, r |
| llm_model | string | yes | The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model |
| conversation_id | string | no | Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep |
Run a full Growth Audit — three linked strategic reports for a product. Unlike analyze_competitor (a single 15-signal intelligence snapshot), a Growth Audit produces an Executive Summary + a Diagnosis Report + a 30-day Action Plan, grounded in real channel/tactic playbooks. Best for 'how do I grow THIS product' rather than 'what is this competitor doing'. Takes ~4-6 minutes.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| url | string | yes | — |
| product_name | no | — | |
| lang | no | — | |
| context | string | yes | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, r |
| llm_model | string | yes | The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model |
| conversation_id | string | no | Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep |
Fetch a Growth Audit's three reports (Executive Summary, Diagnosis, Action Plan) as Markdown. Args: job_id: ID from run_growth_audit() (starts with 'ga-') Returns: {status, reports: {executive_summary, diagnosis_report, action_plan}} while running, only {status, progress} is returned.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| job_id | string | yes | — |
| context | string | yes | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, r |
| llm_model | string | yes | The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model |
| conversation_id | string | no | Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep |
Browse Analook's public competitor-intelligence report gallery. Returns recently published public reports (product name, domain, category, and a link). No authentication or credits required — a fast way to discover existing analyses before spending a credit on a fresh one. Args: category: Optional filter, e.g. 'AI / Agents', 'Dev Tools', 'Crypto / Web3',
| Parameter | Type | Required | Notes |
|---|---|---|---|
| category | no | — | |
| context | string | yes | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, r |
| llm_model | string | yes | The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model |
| conversation_id | string | no | Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep |
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 Analook — Competitor Intelligence or to call it, at any volume.
Call allowance · this installenforced at the gateway
Monthly allowance, in calls
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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: the repository linked on this page is where this record was collected from, not a copy of what the address serves, so it is not graded in its place. 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 1.0.2.
1.0.2
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 Analook — Competitor Intelligence 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.