Précis Finance MCP
Public read-only Précis Finance MCP demo with synthetic data; no account or credentials required.
| Endpoint | https://mcp.precis.finance/mcp (streamable-http) |
|---|---|
| Registry version | 0.3.0 |
| Now | 20 tools · grade C (69) · pin ts_cff7fdc063a6ad11f6d51694ae31ebd8 · protocol 2025-06-18 |
| First / last listed | 2026-10-28 01:54 UTC / 2026-10-28 01:54 UTC |
| Grade over time | 2026-10-28: C (69), 20 tools |
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Tools: precis_orientation list_scenarios list_kpis list_inspection_sources get_inspection_schema inspect_rows run_statement run_statement_data run_metric run_metric_data search_hierarchy list_dimensions list_variants eval_chart_transform export_dataset get_file_download list_load_history get_load_status list_bindings get_binding
precis_orientation | Call this first. Returns how to use Précis over this connector: the data model (scenarios, metrics, statements, dimensions), the reporting-tool variants, and how to build charts. Read it before composing queries. params: none |
list_scenarios | List the available planning scenarios and their status. params: none |
list_kpis | Browse the metric catalogue — metric keys, formats, domains, and the dimensions available per metric. params: none |
list_inspection_sources | List the row-level sources available for inspection. params: none |
get_inspection_schema | Get the column schema for an inspection source. params: source_key* |
inspect_rows | Inspect the row-level detail behind a figure, from an enabled inspection source. Returns a capped sample for reasoning plus a grid for the user. params: source_key*, scenario_id*, filters, columns, limit, period_start, period_end |
run_statement | Run a financial statement — P&L, variance report, or executive summary. Rows are statement lines (Revenue, Direct Cost, Gross Margin, …); columns are scenarios. Supports an optional dimension breakdown (e.g. by period or cost centre). For an unspecified general P&L, prefer `full_pnl` when it is listed by precis_orientation. Give every scenario a concise, user-facing `alias` such as Actuals, Budget params: statement, scenarios, period_start, period_end, filters, dimensions, scale, decimals |
run_statement_data | Run a financial statement — P&L, variance report, or executive summary. Rows are statement lines (Revenue, Direct Cost, Gross Margin, …); columns are scenarios. Supports an optional dimension breakdown (e.g. by period or cost centre). For an unspecified general P&L, prefer `full_pnl` when it is listed by precis_orientation. Give every scenario a concise, user-facing `alias` such as Actuals, Budget params: statement, scenarios, period_start, period_end, filters, dimensions, scale, decimals |
run_metric | Break one or more metrics down by a dimension — revenue by project, utilisation by employee, headcount trends, GL account drill-down. Rows are the dimension; columns are metrics × scenarios. Pass `scenarios` explicitly and give every scenario a concise, user-facing `alias` such as Actuals, Budget, Variance, or Var %. Returns a formatted table with structured data. The widget already displays this params: metrics*, scenarios, period_start, period_end, filters, dimensions, scale, decimals |
run_metric_data | Break one or more metrics down by a dimension — revenue by project, utilisation by employee, headcount trends, GL account drill-down. Rows are the dimension; columns are metrics × scenarios. Pass `scenarios` explicitly and give every scenario a concise, user-facing `alias` such as Actuals, Budget, Variance, or Var %. Returns the raw figures (and a `data_ref`) for your own analysis or to build a ch params: metrics*, scenarios, period_start, period_end, filters, dimensions, scale, decimals |
search_hierarchy | Search the dimension hierarchies (cost centres, accounts, …) to find valid codes and ids before composing a query. params: query, dimension, limit |
list_dimensions | List the dimensions defined in the model — keys, labels, and kinds (leaf / derived / ragged hierarchy). Catalogue metadata only; use search_hierarchy to list a dimension's members. params: none |
list_variants | List the what-if variants of a scenario. params: scenario_id* |
eval_chart_transform | Create a chart from data_refs (an array of snapshot IDs), a bounded JavaScript function, and chart_spec. Supports line, bar, area, waterfall, scatter, horizontal_bar, forecast_line, cohort_heatmap and sparkline_row. Query first and inspect rows; the transform takes one result per ref and returns flat rows. params: data_refs*, transform_code*, chart_spec* |
export_dataset | Export a cached data_ref to json or xlsx without rerunning the query; returns a temporary file and download link. params: data_ref*, format* |
get_file_download | Renew a download capability for an available, owned artifact. params: file_id* |
list_load_history | List data-load attempts from the ingestion audit trail — when each dataset landed, with what status. Answers "is April in yet?" / "when was this data last loaded?". params: binding_id, dataset_id, period, status, limit |
get_load_status | Fetch one data load's full detail by load_id — timestamps, status, rows landed, and any error message. params: load_id* |
list_bindings | List the configured data feeds (ingestion bindings) with their schedule — which datasets load, from where, how often. params: source_id, target |
get_binding | Fetch one data feed's full configuration: source, target dataset, schedule, and extract parameters. params: binding_id* |
Entries describe changes in tool definitions. They are not statements about a server, its quality or its author. The grade measures how the tool definitions fit model providers (token cost, schema compatibility, confusable names) as scored by the ToolFit engine at the time of the listing. JSON: append .json. Opt-out: how or hello@youraitools.co.