MCP

Retrocast MCP

The Retrocast MCP server exposes your Retrocast workspace as tools, so an MCP client can ingest a dataset, inspect its columns, run forecasts and backtests, score the results and open the run in the app — without you writing any HTTP calls.

It is a different server from the Docs MCP, which only searches this documentation and needs no account. This one works against your own data, so it signs you in first.

Who can connect


Endpoint	`https://retrocast-backend-prod.fly.dev/mcp`
Transport	Streamable HTTP (stateless)
Authentication	OAuth 2.0 — your MCP client runs the flow for you
Requires	A Retrocast account. Free accounts get 20 forecasts a day; backtesting is available on paid plans

Clients discover the authorization server from /.well-known/oauth-protected-resource/mcp; there is nothing to register or paste by hand.

No account yet? Sign up for Retrocast. The free tier covers 20 forecasts a day, which is enough to connect a client and work through the dataset and forecasting tools below. Backtesting is available on paid plans.

Connect a client

Claude, Codex and Cursor are the supported clients today. Other MCP clients aren't tested against this server yet — tell us which one you need and we'll look at it.

Claude Code:

Code
claude mcp add --transport http retrocast https://retrocast-backend-prod.fly.dev/mcp

Codex CLI:

Code
codex mcp add --transport http retrocast https://retrocast-backend-prod.fly.dev/mcp

Claude Desktop and the Codex app read a JSON config instead:


Code
{
  "mcpServers": {
    "retrocast": {
      "url": "https://retrocast-backend-prod.fly.dev/mcp"
    }
  }
}

Cursor needs the OAuth client spelled out in ~/.cursor/mcp.json:


Code
{
  "mcpServers": {
    "retrocast-mcp": {
      "url": "https://retrocast-backend-prod.fly.dev/mcp",
      "auth": {
        "CLIENT_ID": "PJdmQfpYABFfWspX"
      }
    }
  }
}

The first call opens a browser window for the OAuth consent step. After that the client refreshes the token on its own.

Accounts belonging to more than one organisation aren't supported yet — a connection resolves against your own. If you need multi-organisation access, get in touch.

Tools

Everything below runs against your own organisation's data. Read-only tools are marked as such by the server, so clients that ask before mutating only prompt on the ones that write.

Datasets

Tool	Purpose
`upload_dataset`	Ingest a CSV or Parquet file. Returns a presigned upload target — PUT the bytes, then call `confirm_dataset_upload`.
`confirm_dataset_upload`	Finalise an upload: analyse, commit column roles, poll until the dataset is `ready`.
`create_dataset_from_link`	Ingest a presigned Parquet URL in one call, no upload round-trip.
`list_datasets`	Browse your datasets, newest first, paginated.
`get_dataset`	One dataset's status, column roles and readiness.
`get_dataset_columns`	Columns with types, flags, and the index/target suggested at analyse time.
`update_dataset_defaults`	Correct the default index or target column on a ready dataset.
`list_example_datasets`	Curated example datasets (`ex_…`) to try the workflow on.
`detect_hierarchy`	Infer categorical nesting (for example region → store → SKU).
`column_values`	Distinct values of one column.
`search_dataset_values`	Find which column holds a label, by searching every text column.
`query_timeseries`	The gap-filled target series as rows.

upload_dataset never streams file bytes through the model or the server: it hands back a self-signed storage URL that you PUT to directly. Uploads store no default index or target, so pass the suggestion you want as an explicit datetime_column / target_column — or set them once with update_dataset_defaults.

Covariates

Tool	Purpose
`detect_covariate_roles`	Suggest how a covariate dataset's columns map onto a target.
`create_covariate_attachment`	Attach a covariate dataset to a target with column roles.
`list_covariate_attachments`	List attachments, optionally filtered by target.

Uploading a covariate dataset is out of scope for now — attach one that is already in the workspace.

Forecasting and backtesting

Tool	Purpose
`create_forecast`	Synchronous forecast. Accepts attached, inline and built-in covariates.
`run_backtest`	Synchronous backtest over historical cutoffs. Returns run metadata and pooled metrics.
`list_backtest_runs`	Browse runs with per-run metrics merged in.
`get_backtest_run`	One run's metadata and scalar metrics.
`list_backtest_series_metrics`	Per-series metrics — worst series by WAPE, or metrics rolled up by dimension.
`list_backtest_cutoff_metrics`	Per-cutoff WAPE/MAE/MAPE, sortable and filterable by date window.
`list_backtest_cutoff_results`	Per-cutoff actuals, forecasts and quantile bands, paged.
`export_backtest_csv`	Full-run predictions as CSV, via a short-lived download URL.
`compare_backtest_runs`	Deterministic comparison of 2–6 single-series runs, joined on forecast creation date.

The backtest tools are available on paid plans. create_forecast is on every plan.

A grouped run returns pooled metrics only. Per-member figures live in list_backtest_series_metrics — which also supplies the series_id the cutoff-grain tools need. Metrics are fractions, not percentages.

Tool	Purpose
`score_forecast`	Score a forecast against actuals over an evaluation frame.
`score_forecast_arrays`	Score aligned `{forecasts, actuals, index}` arrays over an optional date range.
`plot_time_series`	Render a brand-styled chart PNG. Returns the image plus a short-lived download URL.
`create_share_url`	Build a link that opens a dataset in Retrocast at a given mode, model, scope, horizon and cutoff.

create_forecast, run_backtest and get_backtest_run lead with a plain-language reading of the result — horizon, interval, which level to trust — and attach it as structured content, with the compacted raw payload after it. The backtest tools include an app_url that opens the run focused in the app.

Guided workflows

Two prompts encode the method rather than leaving it to the model:

forecast_workflow — detect the hierarchy, backtest each level, forecast at the level that backtests best, and recommend it citing that evidence.
forecast_report — profile the data, forecast at your current operating points, score every forecast identically, and write a like-for-like accuracy comparison.

Both take an optional dataset_id.

Interactive forecast viewer

Clients that support MCP Apps render create_forecast results as a live chart instead of JSON. Every other client gets the same summary and payload as text — nothing is hidden behind the viewer.

Errors

Status	Meaning
`401`	Missing or invalid token. Reconnect so the client can run the OAuth flow again.
`403`	Authenticated, but this account isn't allowed to use the server.
`404`	Unknown dataset, run or attachment.
`422`	Invalid tool arguments.
`429`	Rate limited, or the day's free-tier forecasts are used up.

Getting help

Ask in the chat inside Retrocast, or email [email protected].

Last modified on September 10, 2026

MCP

Retrocast MCP

It is a different server from the Docs MCP, which only searches this documentation and needs no account. This one works against your own data, so it signs you in first.

Who can connect


Endpoint	`https://retrocast-backend-prod.fly.dev/mcp`
Transport	Streamable HTTP (stateless)
Authentication	OAuth 2.0 — your MCP client runs the flow for you
Requires	A Retrocast account. Free accounts get 20 forecasts a day; backtesting is available on paid plans

Clients discover the authorization server from /.well-known/oauth-protected-resource/mcp; there is nothing to register or paste by hand.

Connect a client

Claude, Codex and Cursor are the supported clients today. Other MCP clients aren't tested against this server yet — tell us which one you need and we'll look at it.

Claude Code:

Code
claude mcp add --transport http retrocast https://retrocast-backend-prod.fly.dev/mcp

Codex CLI:

Code
codex mcp add --transport http retrocast https://retrocast-backend-prod.fly.dev/mcp

Claude Desktop and the Codex app read a JSON config instead:


Code
{
  "mcpServers": {
    "retrocast": {
      "url": "https://retrocast-backend-prod.fly.dev/mcp"
    }
  }
}

Cursor needs the OAuth client spelled out in ~/.cursor/mcp.json:


Code
{
  "mcpServers": {
    "retrocast-mcp": {
      "url": "https://retrocast-backend-prod.fly.dev/mcp",
      "auth": {
        "CLIENT_ID": "PJdmQfpYABFfWspX"
      }
    }
  }
}

The first call opens a browser window for the OAuth consent step. After that the client refreshes the token on its own.

Accounts belonging to more than one organisation aren't supported yet — a connection resolves against your own. If you need multi-organisation access, get in touch.

Tools

Everything below runs against your own organisation's data. Read-only tools are marked as such by the server, so clients that ask before mutating only prompt on the ones that write.

Datasets

Tool	Purpose
`upload_dataset`	Ingest a CSV or Parquet file. Returns a presigned upload target — PUT the bytes, then call `confirm_dataset_upload`.
`confirm_dataset_upload`	Finalise an upload: analyse, commit column roles, poll until the dataset is `ready`.
`create_dataset_from_link`	Ingest a presigned Parquet URL in one call, no upload round-trip.
`list_datasets`	Browse your datasets, newest first, paginated.
`get_dataset`	One dataset's status, column roles and readiness.
`get_dataset_columns`	Columns with types, flags, and the index/target suggested at analyse time.
`update_dataset_defaults`	Correct the default index or target column on a ready dataset.
`list_example_datasets`	Curated example datasets (`ex_…`) to try the workflow on.
`detect_hierarchy`	Infer categorical nesting (for example region → store → SKU).
`column_values`	Distinct values of one column.
`search_dataset_values`	Find which column holds a label, by searching every text column.
`query_timeseries`	The gap-filled target series as rows.

Covariates

Tool	Purpose
`detect_covariate_roles`	Suggest how a covariate dataset's columns map onto a target.
`create_covariate_attachment`	Attach a covariate dataset to a target with column roles.
`list_covariate_attachments`	List attachments, optionally filtered by target.

Uploading a covariate dataset is out of scope for now — attach one that is already in the workspace.

Forecasting and backtesting

Tool	Purpose
`create_forecast`	Synchronous forecast. Accepts attached, inline and built-in covariates.
`run_backtest`	Synchronous backtest over historical cutoffs. Returns run metadata and pooled metrics.
`list_backtest_runs`	Browse runs with per-run metrics merged in.
`get_backtest_run`	One run's metadata and scalar metrics.
`list_backtest_series_metrics`	Per-series metrics — worst series by WAPE, or metrics rolled up by dimension.
`list_backtest_cutoff_metrics`	Per-cutoff WAPE/MAE/MAPE, sortable and filterable by date window.
`list_backtest_cutoff_results`	Per-cutoff actuals, forecasts and quantile bands, paged.
`export_backtest_csv`	Full-run predictions as CSV, via a short-lived download URL.
`compare_backtest_runs`	Deterministic comparison of 2–6 single-series runs, joined on forecast creation date.

The backtest tools are available on paid plans. create_forecast is on every plan.

Tool	Purpose
`score_forecast`	Score a forecast against actuals over an evaluation frame.
`score_forecast_arrays`	Score aligned `{forecasts, actuals, index}` arrays over an optional date range.
`plot_time_series`	Render a brand-styled chart PNG. Returns the image plus a short-lived download URL.
`create_share_url`	Build a link that opens a dataset in Retrocast at a given mode, model, scope, horizon and cutoff.

Guided workflows

Two prompts encode the method rather than leaving it to the model:

forecast_workflow — detect the hierarchy, backtest each level, forecast at the level that backtests best, and recommend it citing that evidence.
forecast_report — profile the data, forecast at your current operating points, score every forecast identically, and write a like-for-like accuracy comparison.

Both take an optional dataset_id.

Interactive forecast viewer

Clients that support MCP Apps render create_forecast results as a live chart instead of JSON. Every other client gets the same summary and payload as text — nothing is hidden behind the viewer.

Errors

Status	Meaning
`401`	Missing or invalid token. Reconnect so the client can run the OAuth flow again.
`403`	Authenticated, but this account isn't allowed to use the server.
`404`	Unknown dataset, run or attachment.
`422`	Invalid tool arguments.
`429`	Rate limited, or the day's free-tier forecasts are used up.

Getting help

Ask in the chat inside Retrocast, or email [email protected].

Last modified on September 10, 2026

Retrocast MCP

Who can connect

Connect a client

Tools

Datasets

Covariates

Forecasting and backtesting

Scoring, charts and sharing

Guided workflows

Interactive forecast viewer

Errors

Getting help

Retrocast MCP

Who can connect

Connect a client

Tools

Datasets

Covariates

Forecasting and backtesting

Scoring, charts and sharing

Guided workflows

Interactive forecast viewer

Errors

Getting help