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524,660 tools. Updated 2026-09-06 17:03

"Matomo web analytics platform" matching MCP tools:

  • Switch on a group of tools that is not in this session's roster. WORKS ON CLIENTS THAT RE-READ THE TOOL LIST (stdio, the CLI); a host that fixed its roster at connect time — ChatGPT does — will not show the new tools until it reconnects, and this tool says so in its reply rather than reporting a success you cannot use. The connect-time route that always works is `?tools=all` on the server URL. The default roster is every group EXCEPT `ads` and `analytics` and `channel_admin`, which are held out purely on SIZE: paid-campaign management is by far the largest group, most of the total schema weight across eleven ad platforms, and measurement is a third again on top of everything else. Most sessions need neither. Nothing in either is unfinished or unsafe — they are one call away. CALL THIS THE MOMENT YOU NEED ONE. If the user asks to build, budget, target, report on or change an ad campaign on any platform, call enable_tools({groups:['ads']}) first and the tools appear. If they ask about their own site or product analytics, a tag/tracking container, or how a search engine crawls, indexes or ranks their site, call enable_tools({groups:['analytics']}). Groups: core, research, create, channels, channel_admin, analytics, ads, files, workspace — or 'all'. Free, instant, and it never turns anything off.
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  • A grounded snapshot of the org's product so YOU can reason about it. Returns one JSON object with: revenue + top paying accounts (ranked by MRR), web + product analytics headline metrics, the feature list, recent verbatim customer signals (newest first), and open-work counts — each block empty when that source isn't flowing yet. The time-windowed sections (revenue, cost, web + product analytics, feature usage) honour `window` (7 | 30 | 90 days, default 30). Single call, no pagination. Start here to ground, then go deeper with the dedicated list_* reads and the analytics tools. Optional product_id (the org's primary product when omitted).
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  • Provisions a managed MySQL (or MariaDB) database on a dedicated VM on your private network — the relational-database resource (use this instead of create_database when the app needs MySQL/MariaDB, e.g. WordPress, NextCloud, Matomo, many PHP/LAMP apps). Requires a recent plan_managed_datastore. For app deployments, prefer deploy_app database:'managed' with db_engine mysql/mariadb so plan_deploy includes and wires the DB automatically. It is PRIVATE — reachable only from another instance on the same private network, via the DB's internal/private IP (port 3306), not a public address. Get the ids from plan_managed_datastore/list_flavors/list_private_networks/list_keypairs. Provisioning takes ~5 min; poll list_relational_databases until status='ready', then the connection details (private_ip, port 3306, db_name, db_user) are populated. MySQL is created with mysql_native_password auth so older clients/apps connect cleanly. (ClickHouse is a separate resource — use create_clickhouse / list_clickhouse_databases.)
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  • Manage AND report on Meta, Google, TikTok, Reddit, X, LinkedIn, and Microsoft ads. Reporting & analytics — campaign performance, results, spend, ROAS, impressions, clicks, conversions, CPC/CPA: use entity:"results" (Google also supports action:"placements" and "search-terms"). Answers "how are my ads doing" / "what's my spend" / "show campaign performance". Management — connect project accounts and create, edit, or publish supported ad resources. Coverage differs per platform — the exact entities, actions, and params for each platform are documented under adkit_help({ path: "manage <platform>" }). Most mutations create drafts by default; publish:true sends changes live and requires explicit user approval. Use AdKit field names in params (not raw platform fields); pass full request bodies as top-level data. Use platformOverrides for raw fields on supported resources. Unsupported native platform resources and workflows are reachable via the raw platform API: entity:"platform-api-request" action:"mutate" (project opt-in); adkit_feedback is the channel for reporting these AdKit gaps. File uploads: entity:"media" action:"request_upload_url" → PUT the bytes → reference the returned uploadId. For creatives/variants/images inside an ad set, use entity:"ads".
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  • Detect website technology stack: CMS, frameworks, CDN, analytics tools, web servers, languages (via HTTP headers + HTML analysis). Use for passive reconnaissance; for full audit use audit_domain. Free: 30/hr, Pro: 500/hr. Returns {technologies: [{name, category, confidence%, version}]}.
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  • List every Stimulsoft product/platform that has indexed documentation available through this MCP server. Returns a JSON array of { id, name, description } objects covering the full Stimulsoft Reports & Dashboards product line (Reports.NET, Reports.WPF, Reports.AVALONIA, Reports.WEB for ASP.NET, Reports.BLAZOR, Reports.ANGULAR, Reports.REACT, Reports.JS, Reports.PHP, Reports.JAVA, Reports.PYTHON, Server API, etc.). CALL THIS FIRST when the user's question is ambiguous about which Stimulsoft platform they are using, or when you need to pick a valid `platform` value to pass into `sti_search`. The returned platform `id` values are the exact strings accepted by the `platform` parameter of `sti_search`. This tool is cheap (no OpenAI call, no vector search) — call it freely whenever you are unsure about platform naming.
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Matching MCP Servers

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    Enables LLMs to directly query a Matomo analytics instance, execute reporting methods, fetch historical trends, report metadata, and dynamically generated chart images through typed MCP tools.
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Matching MCP Connectors

  • Ask about your website traffic in chat.

  • Web Analitiği MCP sunucusu — in-house on-page SEO denetimi (robots.txt + SSRF korumalı crawl),…

  • Read-only. Use to query Dreamlit analytics for overview metrics, notification rows, recipient engagement, or workflow run rows with filters, sorting, and cursor pagination. Returns bounded structured analytics data, effective query metadata, pagination details when rows are included, and relevant app URLs. Do not use for CSV exports, bulk dumps, workflow edits, publishing, or low-level database access.
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  • [Read] Search and analyze X/Twitter discussions for a topic, with tweet-level evidence and cited posts. Aggregate social mood, sentiment score, or positive/negative split -> get_social_sentiment. Open-web pages -> web_search. Multi-platform social search -> search_ugc. Read-only public research data. No account access, no order placement or fund transfers. Not investment advice.
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  • List the platform connectors set up on this Autario account | Google Search Console, Google Analytics 4 (GA4), Google Ads, Meta Ads, Facebook Pages, Instagram, TikTok, TikTok Ads, YouTube, LinkedIn, Shopify, Stripe, Bing Webmaster Tools, OpenAI and Anthropic usage. Each entry carries its live dataset_id (queryable via query_dataset), datasets[] (ALL datasets the connector materialized | multi-report connectors produce one per report), refresh interval, and last refresh time. Use this whenever a user asks about "my Search Console data", "my ad spend", "my store orders" or wants a cross-platform weekly report: it tells you which platforms are actually connected and which table holds each one. Connectors are created by the account owner in the Autario UI (autario.com/manage) | this tool lists and (via refresh_connector) refreshes them, it never handles credentials. Requires AUTARIO_API_KEY.
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  • Return canonical brand metadata for citation. Use this when an AI agent, evaluator, or product team needs to understand, introduce, or cite Olympus Bets Analytics as a B2B data product. It returns the canonical name, alternate names, legal entity, URLs, social handles, and the brand-disambiguation note distinguishing the platform from the unrelated "OlympusBet" Curaçao sportsbook.
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  • Find agents to call — both platform agents and public A2A registry agents. Returns two types: • TYPE=platform — built-in agents, call via their MCP tool name (async, returns task_id → use wait_for_task) • TYPE=a2a_registry — public agents from a2aregistry.org, call via a2a_call_agent(agent_url=ENDPOINT, message='...') (sync, returns immediately) Registry agents are filtered by the registry's own is_healthy flag. Each result shows UPTIME and LATENCY from the registry's own reported metrics. Free. Args: query: Keywords to filter by capability (e.g. 'weather', 'web scraping', 'research'). Leave empty to browse top agents. limit: Max results to return (default 10, max 25).
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  • Assemble one person's entire public footprint into a single sourced profile: identity, contact details, social accounts unified across platforms, work history, education, relatives, locations, and web mentions - every claim linked to the page it came from. Prefer this over reading search results yourself when you need the whole picture of one person rather than a single fact; it does the cross-platform correlation that a web search leaves to you. Pass a name plus the headline or username from search_people so the right individual is profiled. Repeat profiles are served from a shared cache: free and instant. Public sources only - never private accounts or breach data.
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  • Route a natural-language intent to the right platform on the ComOS network — the first thing to call. Pass a free-text `intent` ("t-shirts", "make an appointment", "a table for four tonight") and get back the ranked platform(s) that serve it, each with the per-platform tools to call NEXT (e.g. bookings → appointment_search). This returns a ROUTE, not a transaction: it tells you where to go; you then act on that platform with the chosen tenant. An intent no platform serves returns an empty route (unroutable: true), never a silent default. Fast and deterministic — the same intent always routes the same way. Returns: A route: ranked platforms (platform_id, label, why_matched, score, entry_points) plus unroutable:true when no platform serves the intent. Example: call federation_search with arguments {}.
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  • Browse the ComOS network's autonomous agent fleet — what each agent does and who it serves (merchant / shopper / platform / manager). Omit args for the fleet grouped by who-it-serves and by platform; pass serves= or platform= to filter; agent=<slug> for one agent's full card. Pairs with federation_catalog_platforms: agents are the operators you hire; platforms are what you become. Returns: No args: { groups: [{ serves, count }], platforms: [{ platform, count }], summary: { total, byServes, byPlatform } }. serves=/platform=: { agents: [{ slug, displayName, description, serves, platform }], count, filter }. agent=<slug>: { agent: { slug, displayName, description, serves, platform, repo } }. Example: call federation_catalog_agents with arguments {}.
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  • Analytics snapshot for Substrate or Polkadot activity in an indexed window, with event, call, and extrinsic counts plus top event and call names. COMMON USER ASKS: - Polkadot activity snapshot - Big picture for Polkadot activity - How is Polkadot doing? FIRST CHOICE FOR: - Polkadot activity analytics in an indexed window - how Polkadot is doing in an indexed window - analytics snapshot for Polkadot or another Substrate network in an indexed window WHEN TO USE: - You want Polkadot activity analytics in a selected indexed window. - You want to ask "how is Polkadot doing in this indexed window?" and get an analytics answer rather than just network freshness metadata. - You want a quick Substrate network snapshot or health check. - You want top pallet events and calls rather than raw rows. - You want to know how a Substrate network is doing in the selected indexed window. DON'T USE: - You need full raw event or call records. EXAMPLES: - Polkadot activity snapshot: {"network":"polkadot","timeframe":"1h"} - Big picture for Polkadot activity: {"network":"polkadot","timeframe":"1h"} - How is Polkadot doing?: {"network":"polkadot","timeframe":"6h"}
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  • Get aggregate statistics about missions on the HomeVisto platform. Returns total counts, status breakdown, and average bounty information. Useful for understanding platform activity.
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  • Run a constrained business-level analytics query without exposing schema details. This is the default fallback for bespoke rankings, counts, snapshots, and timelines across owners, firms, and correspondents. Prefer this before chaining search, summary, or web research tools for aggregate business questions.
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  • [Read] Search the platform news index for headlines, news items, and briefing-style result lists. Open-web research with synthesized answers and cited external pages -> web_search. Event catalog with event_id -> get_latest_events. Read-only public research data. No account access, no order placement or fund transfers. Not investment advice.
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  • Verifies that a mobile or CTV app bundle ID actually exists in the relevant app store — used to detect bundle spoofing in bid requests. Platform support (v1): - `ios`: verified live via Apple's iTunes Lookup API. - `android`: verified live via the Google Play store listing page. - `ctv_*` / `web`: no public store API — returns verified=null. Inputs: - `bundle_id` (body, required): e.g. `com.nytimes.NYTimes`. - `platform` (body, required): ios | android | ctv_roku | ctv_fire | ctv_samsung | ctv_lg | ctv_vizio | web. - `claimed_developer` (body, optional): checked against the store listing. Returns: - `verified`: true | false | null (not checkable on this platform). - `store_listing`: name, developer, developer_match, store_url.
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  • Dispatch to the SOCIAL LISTENING RESEARCHER — multi-platform community-signal interpretation. Use for: "what are practitioners saying about X across platforms / what jargon is emerging in field Y / what is the cross-platform discourse around brand/topic Z". Treats T3 community sources as primary data, distinguishes cross-platform patterns from single-platform noise. ≥3 platforms sampled per brief. Returns: Signal map (Signal / Platforms / Volume / Sentiment + recency) + Per-platform evidence trail + Cross-platform vs single-platform classification + Confidence flag + Sources. NOT for: single-source thematic work (use dispatch_qualitative_researcher) / numerical sentiment effect sizes (use dispatch_quantitative_researcher). ASYNC version: returns { job_id } immediately, the specialist runs durably on a Vercel Workflow (no 300s timeout). Use this version when the specialist is expected to take >90s. Call get_dispatch_result(job_id) periodically (respect wait_ms_hint in the response) until status === 'completed' or 'failed'. Idempotent: same brief + same org reuses the same job_id, so retries don't fan out duplicate runs.
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  • List the platform keys present across the tldr-pages cheatsheet collection (common, linux, osx, windows, android, sunos, freebsd), derived from the tldr-pages index published on GitHub. Returns the sorted set of platform values that the page, commands, and search tools in this pack accept. Answers which platform value to pass when looking up a tldr command cheatsheet.
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