# tlly (remote · tlly.dev)

Hosted dashboards and scheduled data jobs for AI agents, with thresholds, alerts and share links.

- Trust score: 75/100 (medium)
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-11-05

## Components

- remote · `tlly.dev`: 75/100 (this document), [markdown](https://verifymcp.io/servers/dev-tlly-tlly/tlly.md), [page](https://verifymcp.io/servers/dev-tlly-tlly/tlly)

## Channel facts

- Endpoint: `https://tlly.dev/mcp`
- Transports: `streamable-http`
- Auth: `required`
- Version: `1.0.0`

## 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 2026-11-05.

- **Endpoint Security**: 83/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - Authorisation is enforced on tool calls, advertised via RFC 9728 protected-resource metadata. Discovery is public, which costs nothing: no tool can be invoked without a token.
  - HTTPS enforcement could not be verified: the plaintext port answered with HTTP 405, which proves neither a plaintext path nor enforcement.
  - The HSTS (Strict-Transport-Security) header is present.
  - DNSSEC check failed: this domain isn't protected by DNSSEC.
  - The authorisation server offers only Dynamic Client Registration (RFC 7591), which MCP 2026-07-28 deprecated in favour of Client ID Metadata Documents.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 74/100
  - 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).
  - AI-judged instruction clarity (good).
  - Context-footprint check failed: tool/resource definitions use about 10316 tokens (~194/item across 53 items; 30 tools + 23 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 13/100
  - Stability observed for 4 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 97/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 91% of tool parameters carry a description.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - All 5 tool(s) whose name or description implies an irreversible operation declare an MCP destructiveHint annotation.
  - An AI judge read all 32 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 60/100
  - Spec-recency check failed: implements MCP spec 2025-06-18; the latest is 2026-07-28.

## Install

### How do I install the tlly MCP server?

tlly is a hosted endpoint at https://tlly.dev/mcp, so there is nothing to install locally. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

### Claude

```bash
claude mcp add --transport http dev-tlly-tlly 'https://tlly.dev/mcp'
```

### Cursor

```json
{
  "mcpServers": {
    "dev-tlly-tlly": {
      "url": "https://tlly.dev/mcp"
    }
  }
}
```

### VS Code

```json
{
  "servers": {
    "dev-tlly-tlly": {
      "type": "http",
      "url": "https://tlly.dev/mcp"
    }
  }
}
```

### Codex

```toml
[mcp_servers.dev-tlly-tlly]
url = "https://tlly.dev/mcp"
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "dev-tlly-tlly": {
      "type": "remote",
      "url": "https://tlly.dev/mcp",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add dev-tlly-tlly --url 'https://tlly.dev/mcp' --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  dev-tlly-tlly:
    url: "https://tlly.dev/mcp"
```

### Netclaw

```json
{
  "McpServers": {
    "dev-tlly-tlly": {
      "Transport": "http",
      "Url": "https://tlly.dev/mcp"
    }
  }
}
```

### Vellum

```bash
assistant mcp add dev-tlly-tlly -t streamable-http -u 'https://tlly.dev/mcp'
```

### Other

```json
{
  "mcpServers": {
    "dev-tlly-tlly": {
      "type": "http",
      "url": "https://tlly.dev/mcp"
    }
  }
}
```

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.

### 2026-11-05 (score 75, +1)

No change was recorded against any check on this day. Stability & Change Management went from 10 to 13. That category is still filling its 30-day observation window: 3 days of observed history at the previous scan, 4 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-11-03 (score 74, +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.

### 2026-11-02 (score 73, 0)

- [functional improvement] Stability: unverified → 0.03

### 2026-11-01 (score 73, +43)

- [security improvement] Authorization: unverified → pass
- [security improvement] Injection markers: unverified → pass
- [security] First check of Judged manipulation: pass
- [security] First check of Authorization: partial
- [functional regression] MCP protocol: unverified → fail
- [functional improvement] Schema quality: unverified → 100
- [functional improvement] Tool coverage: unverified → 100
- [functional] First check of Schema quality: fail
- [functional] First check of Schema quality: fail
- [functional] First check of Tool coverage: 91
- [functional] First check of Destructive annotations: 100
- [functional] First check of Schema quality: good

### 2026-10-30 (score 30)

First indexed and scored.

## MCP tools (30)

### `create_dashboard` (~1140 tokens)

Create dashboard

Create a hosted dashboard; returns its public URL. Dashboard spec: {"title": str, "description"?: str, "range"?: "1m"|"3m"|"6m"|"ytd"|"1y"|"2y"|"5y"|"10y"|"max", "theme"?: "auto"|"light"|"dark" (default mode; auto follows the viewer's system and viewers can switch), "layout"?: "auto"|"overview"|"detail" (only the default for panels without "display": overview makes them tiles, detail makes them charts, auto makes them tiles above 8 panels), "visibility"?: "public"|"private" (default public: anyone with the link; private: only members of this account signed in to tlly.dev, so embeds and shared links stop working for others), "panels": [{"title"?: str,
"series": "name" | ["a","b"], "type"?: "line"|"area"|"bar"|"stat"|"gauge"|"bargauge"|"pie"|"heatmap"|"table", "unit"?: str, "note"?: str, "stale_after_days"?: num,
"thresholds"?: {"red_above"?, "yellow_above"?, "yellow_below"?, "red_below"?}, "range"?: (as above, overrides the dashboard's),
"section"?: str (starts a new titled section at this panel), "views"?: bool (show the Level / Y/Y % / Index buttons; default: shown unless the unit is already a rate like %, y/y or pp), "display"?: "tile"|"chart" (tile: a compact number with a sparkline, click for the full chart; chart: a card with the full chart; mix them freely, e.g. tiles for the many supporting numbers and charts for the few that need their history), "headline"?: bool (show as a big number at the top of the dashboard, under a status strip; use for the 3-6 most important), "width"?: "half"|"full", "scale"?: "linear"|"log",
"id"?: str (stable panel id, e.g. pn_abc123XYZ012; keep existing ids when editing so alerts stay attached),
"right_axis"?: [series names] (line, area and bar charts: draw these series against a second y axis on the right, for series of different sizes or units; at least one stays on the left), "right_unit"?: str (unit of the right axis; "unit" is the left's), "left_label"?/"right_label"?: str (≤40 chars, a title written vertically along the lef…

Input parameters:

- `spec` (object, required): dashboard spec

### `update_dashboard` (~1277 tokens)

Update dashboard

Replace a dashboard's spec (URL stays the same). Every update is saved as a numbered version. With "draft": true it is saved without going live: viewers keep seeing the live version, members can preview the draft at the returned preview_url, and publish_dashboard_version makes it live. Use drafts for larger changes and publish when the user confirms. Dashboard spec: {"title": str, "description"?: str, "range"?: "1m"|"3m"|"6m"|"ytd"|"1y"|"2y"|"5y"|"10y"|"max", "theme"?: "auto"|"light"|"dark" (default mode; auto follows the viewer's system and viewers can switch), "layout"?: "auto"|"overview"|"detail" (only the default for panels without "display": overview makes them tiles, detail makes them charts, auto makes them tiles above 8 panels), "visibility"?: "public"|"private" (default public: anyone with the link; private: only members of this account signed in to tlly.dev, so embeds and shared links stop working for others), "panels": [{"title"?: str,
"series": "name" | ["a","b"], "type"?: "line"|"area"|"bar"|"stat"|"gauge"|"bargauge"|"pie"|"heatmap"|"table", "unit"?: str, "note"?: str, "stale_after_days"?: num,
"thresholds"?: {"red_above"?, "yellow_above"?, "yellow_below"?, "red_below"?}, "range"?: (as above, overrides the dashboard's),
"section"?: str (starts a new titled section at this panel), "views"?: bool (show the Level / Y/Y % / Index buttons; default: shown unless the unit is already a rate like %, y/y or pp), "display"?: "tile"|"chart" (tile: a compact number with a sparkline, click for the full chart; chart: a card with the full chart; mix them freely, e.g. tiles for the many supporting numbers and charts for the few that need their history), "headline"?: bool (show as a big number at the top of the dashboard, under a status strip; use for the 3-6 most important), "width"?: "half"|"full", "scale"?: "linear"|"log",
"id"?: str (stable panel id, e.g. pn_abc123XYZ012; keep existing ids when editing so alerts stay attached),
"right_axis"?: [series names] (line, a…

Input parameters:

- `dashboard_id` (string, required): id
- `draft` (boolean): save as a draft version without changing the live dashboard. Chat always drafts, even if this is false.
- `note` (string): optional short description of this version (≤200 characters)
- `replace_thresholds` (boolean): set true only after the user agrees to drop or change an existing colour line
- `spec` (object, required): dashboard spec

### `list_dashboard_versions` (~43 tokens)

List dashboard versions

List a dashboard's saved versions (newest first) with which one is live and a members-only preview URL for each.

Input parameters:

- `dashboard_id` (string, required): id

### `publish_dashboard_version` (~58 tokens)

Publish dashboard version

Make a saved version of a dashboard the live one (also to roll back). The dashboard keeps its URL and visibility.

Input parameters:

- `dashboard_id` (string, required): id
- `version` (integer, required): version number from list_dashboard_versions or update_dashboard

### `rotate_dashboard_url` (~47 tokens)

Rotate dashboard URL

Give a dashboard a new public URL and disable the old one at once (e.g. if a link leaked). Spec and data are unchanged.

Input parameters:

- `dashboard_id` (string, required): id

### `list_dashboards` (~15 tokens)

List dashboards

List dashboards with their URLs.

### `delete_dashboard` (~26 tokens)

Delete dashboard

Delete a dashboard (series data is kept).

Input parameters:

- `dashboard_id` (string, required): id

### `push_points` (~116 tokens)

Write series points

Write dated values to a series (upsert by date). Use when you compute data yourself. Values are numbers, or short text labels for a text series (e.g. a rating or stance; see Data policy). A series' first write fixes its type.

Input parameters:

- `points` (array, required): [{"date":"2026-09-30","value":4.6}] or [{"date":"2026-09-30","value":"AA+"}]
- `series` (string, required): series name, e.g. household_credit_yoy

### `get_series` (~31 tokens)

Read series points

Read the latest points of a series.

Input parameters:

- `limit` (integer)
- `series` (string, required): name

### `list_series` (~32 tokens)

List series

List all series with their type (number or text), point counts and date ranges; text series also list their values.

### `delete_series` (~31 tokens)

Delete series data

Delete all points of a series, or remove a derived series' definition.

Input parameters:

- `series` (string, required): name

### `define_derived` (~440 tokens)

Define derived series

Create or replace a derived series, computed from other series every time it is read (always fresh, stores no points, counts toward the series limit). definition: {"op":"add"|"subtract"|"multiply"|"divide","a":series,"b":series} (matched by date) | {"op":"pct_change"|"diff"|"moving_average"|"rolling_min"|"rolling_max"|"shift","a":series,"n"?:1-1000} (shift: the value n points earlier) | {"op":"scale","a":series,"factor":number} | {"op":"resample","a":series,"to":"M"|"Q","how"?:"last"|"mean"|"sum"|"ffill"} (to month/quarter ends; ffill also fills gaps up to today) | {"op":"mean"|"sum","inputs":[2-20 series]} (dates all inputs have) | {"op":"status","a":series,"red"?:[rule],"yellow"?:[rule]} → text labels red/yellow/green (red if any red rule holds, else yellow if any yellow rule, else green); rule: {"series"?:name (default a; read as of each date of a),"above"|"below":number,"for"?:1-24 (holds for the last k points)} or {"all":[2-10 rules]}; at most 10 rules | {"op":"composite","inputs":[status series],"min_inputs"?:n} → 0-100 score (red 2, yellow 1, green 0) | {"op":"count","inputs":[status series],"value":"red"|"yellow"|"green","share"?:true (percent)}. Inputs may themselves be derived (up to 10 levels; one read may touch at most 200 stored series). Example: a yield-curve spread {"op":"subtract","a":"govt_10y","b":"tbill_3m"}.

Input parameters:

- `definition` (object, required): definition
- `series` (string, required): name for the derived series

### `list_secrets` (~52 tokens)

List secret names

List the names of the workspace's stored secrets (API keys for private sources) and the host each may be sent to. Use one in a job's url, headers or body as {{secret:NAME}}.

### `test_job` (~1135 tokens)

Preview a fetch job

Dry-run a job spec: fetch, extract and transform, return a preview. Saves nothing. Job spec: {"series": name, "cron": "m h dom mon dow" (UTC, at most every 5 min),
"request": {"url", "method"?: "GET"|"POST", "headers"?: {}, "body"?: obj|str,
            "pages"?: {"param": "page", "start"?: 0, "max"?: 1-10} (json with items: bump a query parameter until an empty items array)
                     | {"cursor": "paging.next.after", "into": "after", "max"?: 1-10} (copy that JSON path from each response into the JSON body; stop when it is missing. A cursor that remains after max pages is an error, so a sum is never a partial total. HubSpot CRM search uses this. A json aggregate with no request.pages fails when the body still has another page, paging.next.after, has_more true, links.next, pageInfo.hasNextPage or another next cursor, instead of saving a partial total. Set pages. A response with no next marker is complete.)},
"extract": {"format": "json", "items"?: "path.to.array", "date"?: "field", "value": "field", "value_type"?: "number"|"text",
            "aggregate"?: "count"|"sum"|"mean"|"min"|"max" (records per date, e.g. hourly prices to a daily mean; needs items; all but count need value), "period"?: "D"|"M"|"Q",
            "where"?: [{"field": "path", "equals"|"not_equals": value}] (up to 5, with aggregate). Omit "date" with aggregate to snapshot every matching record as one point on the day of the fetch. String numbers (HubSpot properties.amount) are summed.}
         | {"format": "json_columns", "dates": "path.to.array", "values": "path.to.array", "value_type"?} (two parallel arrays, e.g. Yahoo chart: timestamp + close)
         | {"format": "csv", "date"?: "COLUMN", "value": "COLUMN", "delimiter"?, "value_type"?} (omit date to stamp every row with the fetch day; one value per day, so the last row wins. That does not sum the rows the way a JSON aggregate that omits date does. A history needs a Date column. Make a copy https://docs.google.com/spreadsheets/d/1T…

Input parameters:

- `spec` (object, required): job spec

### `create_job` (~1140 tokens)

Create scheduled job

Schedule a fetch job. It runs once immediately and the result is returned. Job spec: {"series": name, "cron": "m h dom mon dow" (UTC, at most every 5 min),
"request": {"url", "method"?: "GET"|"POST", "headers"?: {}, "body"?: obj|str,
            "pages"?: {"param": "page", "start"?: 0, "max"?: 1-10} (json with items: bump a query parameter until an empty items array)
                     | {"cursor": "paging.next.after", "into": "after", "max"?: 1-10} (copy that JSON path from each response into the JSON body; stop when it is missing. A cursor that remains after max pages is an error, so a sum is never a partial total. HubSpot CRM search uses this. A json aggregate with no request.pages fails when the body still has another page, paging.next.after, has_more true, links.next, pageInfo.hasNextPage or another next cursor, instead of saving a partial total. Set pages. A response with no next marker is complete.)},
"extract": {"format": "json", "items"?: "path.to.array", "date"?: "field", "value": "field", "value_type"?: "number"|"text",
            "aggregate"?: "count"|"sum"|"mean"|"min"|"max" (records per date, e.g. hourly prices to a daily mean; needs items; all but count need value), "period"?: "D"|"M"|"Q",
            "where"?: [{"field": "path", "equals"|"not_equals": value}] (up to 5, with aggregate). Omit "date" with aggregate to snapshot every matching record as one point on the day of the fetch. String numbers (HubSpot properties.amount) are summed.}
         | {"format": "json_columns", "dates": "path.to.array", "values": "path.to.array", "value_type"?} (two parallel arrays, e.g. Yahoo chart: timestamp + close)
         | {"format": "csv", "date"?: "COLUMN", "value": "COLUMN", "delimiter"?, "value_type"?} (omit date to stamp every row with the fetch day; one value per day, so the last row wins. That does not sum the rows the way a JSON aggregate that omits date does. A history needs a Date column. Make a copy https://docs.google.com/spreadsheets/d/1Ty5X3LkY2…

Input parameters:

- `name` (string): optional label
- `spec` (object, required): job spec

### `import_once` (~1161 tokens)

Import data once

Fetch a job spec once and save the result, without scheduling it or using a job slot ("cron" is optional and ignored). Use for one-off dashboards whose data doesn't need to update; points count toward the data quota. Job spec: {"series": name, "cron": "m h dom mon dow" (UTC, at most every 5 min),
"request": {"url", "method"?: "GET"|"POST", "headers"?: {}, "body"?: obj|str,
            "pages"?: {"param": "page", "start"?: 0, "max"?: 1-10} (json with items: bump a query parameter until an empty items array)
                     | {"cursor": "paging.next.after", "into": "after", "max"?: 1-10} (copy that JSON path from each response into the JSON body; stop when it is missing. A cursor that remains after max pages is an error, so a sum is never a partial total. HubSpot CRM search uses this. A json aggregate with no request.pages fails when the body still has another page, paging.next.after, has_more true, links.next, pageInfo.hasNextPage or another next cursor, instead of saving a partial total. Set pages. A response with no next marker is complete.)},
"extract": {"format": "json", "items"?: "path.to.array", "date"?: "field", "value": "field", "value_type"?: "number"|"text",
            "aggregate"?: "count"|"sum"|"mean"|"min"|"max" (records per date, e.g. hourly prices to a daily mean; needs items; all but count need value), "period"?: "D"|"M"|"Q",
            "where"?: [{"field": "path", "equals"|"not_equals": value}] (up to 5, with aggregate). Omit "date" with aggregate to snapshot every matching record as one point on the day of the fetch. String numbers (HubSpot properties.amount) are summed.}
         | {"format": "json_columns", "dates": "path.to.array", "values": "path.to.array", "value_type"?} (two parallel arrays, e.g. Yahoo chart: timestamp + close)
         | {"format": "csv", "date"?: "COLUMN", "value": "COLUMN", "delimiter"?, "value_type"?} (omit date to stamp every row with the fetch day; one value per day, so the last row wins. That does not sum the ro…

Input parameters:

- `spec` (object, required): job spec

### `update_job` (~1145 tokens)

Update scheduled job

Replace a job's spec, or pause it with enabled=false. Job spec: {"series": name, "cron": "m h dom mon dow" (UTC, at most every 5 min),
"request": {"url", "method"?: "GET"|"POST", "headers"?: {}, "body"?: obj|str,
            "pages"?: {"param": "page", "start"?: 0, "max"?: 1-10} (json with items: bump a query parameter until an empty items array)
                     | {"cursor": "paging.next.after", "into": "after", "max"?: 1-10} (copy that JSON path from each response into the JSON body; stop when it is missing. A cursor that remains after max pages is an error, so a sum is never a partial total. HubSpot CRM search uses this. A json aggregate with no request.pages fails when the body still has another page, paging.next.after, has_more true, links.next, pageInfo.hasNextPage or another next cursor, instead of saving a partial total. Set pages. A response with no next marker is complete.)},
"extract": {"format": "json", "items"?: "path.to.array", "date"?: "field", "value": "field", "value_type"?: "number"|"text",
            "aggregate"?: "count"|"sum"|"mean"|"min"|"max" (records per date, e.g. hourly prices to a daily mean; needs items; all but count need value), "period"?: "D"|"M"|"Q",
            "where"?: [{"field": "path", "equals"|"not_equals": value}] (up to 5, with aggregate). Omit "date" with aggregate to snapshot every matching record as one point on the day of the fetch. String numbers (HubSpot properties.amount) are summed.}
         | {"format": "json_columns", "dates": "path.to.array", "values": "path.to.array", "value_type"?} (two parallel arrays, e.g. Yahoo chart: timestamp + close)
         | {"format": "csv", "date"?: "COLUMN", "value": "COLUMN", "delimiter"?, "value_type"?} (omit date to stamp every row with the fetch day; one value per day, so the last row wins. That does not sum the rows the way a JSON aggregate that omits date does. A history needs a Date column. Make a copy https://docs.google.com/spreadsheets/d/1Ty5X3LkY2unxTNGbkq36qDzuuYxQMs…

Input parameters:

- `enabled` (boolean)
- `job_id` (string, required): id
- `spec` (object, required): job spec

### `list_jobs` (~22 tokens)

List jobs

List scheduled fetch jobs with their last run status and any error message.

### `run_job_now` (~36 tokens)

Run job now

Run a scheduled fetch job immediately, store any new points, and return the run result.

Input parameters:

- `job_id` (string, required): id

### `delete_job` (~27 tokens)

Delete job

Delete a job (its series data is kept).

Input parameters:

- `job_id` (string, required): id

### `get_status` (~31 tokens)

Workspace health check

Health check: failing jobs, stale or empty panels, dashboards, storage usage. Call this to verify everything works.

### `get_usage` (~36 tokens)

Storage usage

Storage usage against quotas (data points = values + annotations, series, dashboards, jobs) and the largest series. Check before large writes.

### `add_annotations` (~102 tokens)

Add chart annotations

Attach short dated notes to a series (e.g. 'Policy rate raised to 4.5%'); shown as markers on charts. Single-line plain text, max 280 chars; one note per date (re-adding replaces it); each counts as one data point.

Input parameters:

- `annotations` (array, required): [{"date":"2026-09-25","text":"Policy rate raised to 4.5%"}]
- `series` (string, required): series name

### `list_annotations` (~31 tokens)

List chart annotations

Read the latest annotations of a series.

Input parameters:

- `limit` (integer)
- `series` (string, required): name

### `delete_annotations` (~42 tokens)

Delete chart annotations

Delete annotations of a series on the given dates, or all of them if dates is omitted.

Input parameters:

- `dates` (array)
- `series` (string, required): name

### `set_alert_webhook` (~132 tokens)

Set alert webhook URL

Set or clear the workspace webhook URL for job-failure and dashboard status alerts (pass an empty url to clear). When events fire, tlly POSTs JSON to that URL (Slack and Discord incoming webhooks get a short text payload instead). Events include job_failed, status_changed (keep panel "id" fields in specs so alerts stay attached), and threshold_crossed. Email alerts work without a webhook. Caps: 12 emails and 60 webhooks per account per hour; the same panel is not alerted twice within an hour.

Input parameters:

- `url` (string): https URL, or empty to clear

### `set_panel_alert` (~188 tokens)

Configure panel alerts

Set when one dashboard panel sends alert email and/or a webhook (colour change, threshold cross, or off). trigger: change (default), red, notgreen, above, below, or off; above/below need limit. notify: both, email, or webhook. panel is the 0-based index in the live spec. Saving can send immediately if a limit was just crossed (unless this panel alerted within the last hour). Later sends happen after scheduled fetches. Default change+both removes a custom rule. Does not change colour lines or save a dashboard version.

Input parameters:

- `dashboard_id` (string, required): id
- `limit` (number): required for above and below
- `notify` (string): both, email or webhook
- `panel` (integer, required): 0-based panel index
- `trigger` (string): change, red, notgreen, above, below or off

### `set_stale_alert` (~153 tokens)

Configure stale-data alerts

Configure when tlly sends stale-data alert email and webhooks because a series stopped updating. after: auto (from the job schedule and point spacing, at least two days), off, hours, or a window like 48h or 7d. Use dashboard_id for every series on a dashboard, series for one series, or both for one series on one dashboard. One email and one webhook when it goes quiet; another when a newer point arrives. Counts toward the hourly caps.

Input parameters:

- `after` (string): auto, off, 48h, 7d, or a number of hours
- `dashboard_id` (string): optional dashboard id
- `series` (string): optional series name

### `list_integration_skills` (~165 tokens)

List integration playbooks

List integration setup playbooks (Stripe, Shopify, Sheets, and the other sources tlly can read). A spreadsheet starts from the KPI template. Make a copy https://docs.google.com/spreadsheets/d/1Ty5X3LkY2unxTNGbkq36qDzuuYxQMsuywaTNyzL_pac/copy. Public CSV https://docs.google.com/spreadsheets/d/1Ty5X3LkY2unxTNGbkq36qDzuuYxQMsuywaTNyzL_pac/export?format=csv&gid=1746689811. Downloads /templates/google-sheets.csv and /templates/google-sheets.xlsx. Public: no API key required.

### `get_integration_skill` (~219 tokens)

Read integration playbook

Read one integration playbook by id: what to track, the minimum credential and scopes, the exact tlly job, and gotchas. google-sheets and json-api also return a template field (Make a copy, public CSV, downloads). Make a copy https://docs.google.com/spreadsheets/d/1Ty5X3LkY2unxTNGbkq36qDzuuYxQMsuywaTNyzL_pac/copy. Public CSV https://docs.google.com/spreadsheets/d/1Ty5X3LkY2unxTNGbkq36qDzuuYxQMsuywaTNyzL_pac/export?format=csv&gid=1746689811. Downloads /templates/google-sheets.csv and /templates/google-sheets.xlsx. Public: no API key required. Call this before inventing an API URL or scope.

Input parameters:

- `id` (string, required): skill id from list_integration_skills, e.g. stripe or google-sheets

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/dev-tlly-tlly/tlly#diagnostics

## Score history

- 2026-11-05: 75
- 2026-11-04: 74
- 2026-11-03: 74
- 2026-11-02: 73
- 2026-11-01: 73
- 2026-10-31: 30
- 2026-10-30: 30

## Common questions

### What is the tlly MCP server?

tlly is an MCP server listed in the public MCP registry as dev.tlly/tlly. Hosted dashboards and scheduled data jobs for AI agents, with thresholds, alerts and share links. This page covers its hosted endpoint (https://tlly.dev/mcp).

### Is the tlly MCP server safe to use?

tlly scores 75 out of 100 on VerifyMCP. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

### What tools does the tlly MCP server expose?

tlly exposes 30 tools: create_dashboard, update_dashboard, list_dashboard_versions, publish_dashboard_version, rotate_dashboard_url, and 25 more. Their descriptions and schemas cost roughly 9,073 tokens of context every time the server is loaded.

### Does the tlly MCP server require authentication?

Yes. tlly asked us for credentials when we connected, so you will need to authorise it in your MCP client before it can do anything.

### Is the tlly MCP server still maintained?

tlly is still listed as active in the MCP registry. We last reached this channel on 5 November 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

## Links

- Remote endpoint: https://tlly.dev/mcp
- Repository: https://github.com/FifthsegmentEng/tlly-mcp
- Website: https://tlly.dev/
- Changelog RSS feed: https://verifymcp.io/servers/dev-tlly-tlly/tlly.xml
- Changelog JSON feed: https://verifymcp.io/servers/dev-tlly-tlly/tlly.json
- HTML version of this page: https://verifymcp.io/servers/dev-tlly-tlly/tlly