# ai.mcpanalytics/analytics (remote · api.mcpanalytics.ai)

The statistical analyst in your AI chat — validated, citable, re-runnable analysis of your data.

- Trust score: 72/100 (medium)
- Change this week: +7
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-08-03

## Components

- remote · `api.mcpanalytics.ai`: 36/100, [markdown](https://verifymcp.io/servers/ai-mcpanalytics-analytics/auth0.md), [page](https://verifymcp.io/servers/ai-mcpanalytics-analytics/auth0)
- remote · `api.mcpanalytics.ai`: 72/100 (this document), [markdown](https://verifymcp.io/servers/ai-mcpanalytics-analytics/mcp-api-key.md), [page](https://verifymcp.io/servers/ai-mcpanalytics-analytics/mcp-api-key)

## Channel facts

- Endpoint: `https://api.mcpanalytics.ai/mcp/api-key`
- Transports: `streamable-http`
- Auth: `none`
- Version: `1.0.7`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-08-03.

- **Endpoint Security**: 83/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - Authorisation is enforced on tool calls, but the challenge carries no valid RFC 9728 metadata, so a client cannot discover where to get a token.
  - HTTPS is enforced; there's no plaintext access path.
  - HSTS check failed: the Strict-Transport-Security header is absent.
  - DNSSEC check failed: this domain isn't protected by DNSSEC.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 71/100
  - AI-judged instruction clarity (good).
  - Tool/resource definitions use about 1278 tokens (~85/item across 15 items; 15 tools + 0 resources), lean.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 27/100
  - Stability observed for 8 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 100/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 100% of tool parameters carry a description.
- **Capabilities**: 20/100
  - Spec-recency check failed: implements MCP spec 2024-11-05; the latest is 2026-07-28.

## Install

### Claude

```bash
claude mcp add --transport http ai-mcpanalytics-analytics https://api.mcpanalytics.ai/mcp/api-key
```

### Codex

```toml
[mcp_servers.ai-mcpanalytics-analytics]
url = "https://api.mcpanalytics.ai/mcp/api-key"
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "ai-mcpanalytics-analytics": {
      "type": "remote",
      "url": "https://api.mcpanalytics.ai/mcp/api-key",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add ai-mcpanalytics-analytics --url https://api.mcpanalytics.ai/mcp/api-key --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  ai-mcpanalytics-analytics:
    url: "https://api.mcpanalytics.ai/mcp/api-key"
```

### Other

```json
{
  "mcpServers": {
    "ai-mcpanalytics-analytics": {
      "type": "http",
      "url": "https://api.mcpanalytics.ai/mcp/api-key"
    }
  }
}
```

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-08-02 (score 72, +1)

No change was recorded against any check on this day. Stability & Change Management went from 20 to 23. That category is still filling its 30-day observation window: 6 days of observed history at the previous scan, 7 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-31 (score 71, +4)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-30 (score 67, 0)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-29 (score 67, +1)

No change was recorded against any check on this day. Stability & Change Management went from 7 to 10. That category is still filling its 30-day observation window: 2 days of observed history at the previous scan, 3 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-28 (score 66, +1)

No change was recorded against any check on this day. Stability & Change Management went from 3 to 7. That category is still filling its 30-day observation window: 1 days of observed history at the previous scan, 2 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-27 (score 65, 0)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-26 (score 65)

First indexed and scored.

## MCP tools (15)

### `account_link` (~51 tokens)

Direct link to the right account page for anything not doable in chat — billing, browser upload, report management. Hand the user the link and guide them.

Input parameters:

- `section` (string): Where to send the user

### `about` (~39 tokens)

Platform documentation and info — how it works, tiers, usage.

Input parameters:

- `topic` (string, required): Topic: platform, manual, connectors, or a docs section

### `agent_advisor` (~39 tokens)

AI help desk — which analysis fits your question, interpreting results, fixing errors. Multi-turn.

Input parameters:

- `message` (string, required): Your question or request

### `datasets_upload` (~87 tokens)

Get your data in. Pass `data` as an array of row objects to create the dataset immediately and get a dataset_ref ready for create_analysis; omit it to get an upload link for a file only the user can reach.

Input parameters:

- `data` (array): Rows as an array of flat objects — creates the dataset in one call
- `expires_in` (integer): Token expiration in seconds

### `datasets_list` (~65 tokens)

List and search your uploaded datasets — fuzzy matching on name, description, and tags. Returns each dataset's uuid:// reference for use in create_analysis and run_analysis.

Input parameters:

- `limit` (integer): Max results
- `search` (string): Search by name, description, or tags

### `discover_tools` (~85 tokens)

Browse the analyses you can run — the ones you commissioned plus the platform Standard Library (prebuilt tools; each result tagged source:'own' or 'standard_library'). Plain-language match; no query lists everything, your own first. Nothing fits? Commission it with create_analysis.

Input parameters:

- `query` (string): Plain-language search over your library + the Standard Library; omit to list everything

### `tools_schema` (~33 tokens)

Get an analysis's parameter schema — ALWAYS call before run_analysis.

Input parameters:

- `tool_name` (string, required): Name of the analysis

### `run_analysis` (~69 tokens)

Run an analysis on your data. Returns a shareable interactive report URL — validated statistics you can cite, re-run, and share.

Input parameters:

- `taskList` (object, required): Execution inputs. Call tools_schema first for the analysis-specific fields.
- `tool_name` (string, required): Name of the analysis to run

### `create_analysis` (~282 tokens)

Commission a NEW analysis built for your question. tier is REQUIRED — the user picks. Easiest: fuzzy_request (plain language) + dataset_ref + tier. Snapshot = instant automated report (~2-10 min). JSON = a fast computed answer, numbers + method, re-runnable tool you own (~5 min). Brief = the computed answer on a one-page report — chart, numbers, method (~7 min). Deck = commissioned deep analysis, a durable re-runnable module you own (30-45 min). Failed builds are never billed.

Input parameters:

- `column_mapping` (object): Optional semantic-to-real column map (hint only)
- `dataset_ref` (string): Single-dataset URI: 'uuid://UUID:KEY'
- `datasets_refs` (object): Multi-dataset URIs keyed by role
- `fuzzy_request` (string): Plain-language description of the analysis you want
- `notes` (string): Optional context for the build — constraints, definitions, or preferences the analyst agents should honor
- `specification` (object): Full 11-field spec (legacy path — prefer fuzzy_request)
- `tier` (string): snapshot = instant report (~2-10 min); json = fast computed answer (~5 min, default); brief = one-page report of the answer (~7 min); deck = commissioned re-runnable module (30-45 min)

### `modify_analysis` (~156 tokens)

Modify an EXISTING analysis into a new version — reword the question, swap the method, or add a variable. Pass tool_name + changes (plain language). Rebuilds on the analysis's own dataset by default; the original stays put. Returns pipeline tracking — follow with build_status.

Input parameters:

- `changes` (string, required): What to change, in plain language, e.g. 'also break it down by region' or 'use a random forest instead'
- `dataset_ref` (string): Optional — rebuild against a different dataset ('uuid://UUID:KEY')
- `tier` (string): Optional — change the depth of the new version
- `tool_name` (string, required): The analysis to modify (from discover_tools or your library)

### `build_status` (~65 tokens)

Check a commissioned build in-chat: stage progress, queue position, rejection reason if the data didn't match the objective, honest ETA, report link when delivered.

Input parameters:

- `pipeline_id` (integer): pipeline_id from create_analysis
- `track_token` (string): Token from the tracking URL

### `ask_library` (~42 tokens)

Ask a question across all your delivered analyses — synthesized answer with citations back to specific reports.

Input parameters:

- `question` (string, required): Plain-language question to answer from your report library

### `reports_list` (~57 tokens)

Your report library — every analysis delivered, with status and links. Pass semantic_query to search report content in plain language.

Input parameters:

- `limit` (integer): Max results
- `semantic_query` (string): Natural-language search over your reports' content

### `reports_view` (~39 tokens)

Get a shareable browser link for a report — viewable without authentication.

Input parameters:

- `processing_id` (string, required): Processing ID from run_analysis / reports_list

### `report_cards` (~47 tokens)

Browse a delivered report's individual cards (charts, tables, insights) inline in chat.

Input parameters:

- `processing_id` (string, required): The report's processing id, returned by run_analysis or build_status

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/ai-mcpanalytics-analytics/mcp-api-key#diagnostics

## Score history

- 2026-08-03: 72
- 2026-08-02: 72
- 2026-08-01: 71
- 2026-07-31: 71
- 2026-07-30: 67
- 2026-07-29: 67
- 2026-07-28: 66
- 2026-07-27: 65
- 2026-07-26: 65

## Links

- Remote endpoint: https://api.mcpanalytics.ai/mcp/api-key
- Repository: https://github.com/embeddedlayers/mcp-analytics
- Changelog RSS feed: https://verifymcp.io/servers/ai-mcpanalytics-analytics/mcp-api-key/changelog.xml
- Changelog JSON feed: https://verifymcp.io/servers/ai-mcpanalytics-analytics/mcp-api-key/changelog.json
- HTML version of this page: https://verifymcp.io/servers/ai-mcpanalytics-analytics/mcp-api-key