MCP serverio.github.precis-finance/precis-finance-mcp
Public read-only Précis Finance MCP demo with synthetic data; no account or credentials required.
Overview
Score?
UNRATED 0.810
of what a free look can see, on 30 looks
Looks
35
last 15 hr ago
Tools
17
More info
URL
mcp.precis.finance/mcp
streamable-http
Says it is
precis 0.2.7
protocol 2025-06-18
In the record since
32 days ago
Among servers18,413 with a card
0median 0.606 · this server 0.810 · highest on record 0.8561
Toolsfrom sha256:c9e55ffe4d…dad92e
| Tool | Schema |
|---|---|
| get_binding Fetch one data feed's full configuration: source, target dataset, schedule, and extract parameters. |
input · no output |
| get_inspection_schema Get the column schema for an inspection source. |
input · no output |
| get_load_status Fetch one data load's full detail by load_id — timestamps, status, rows landed, and any error message. |
input · no output |
| 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. |
input · no output |
| list_bindings List the configured data feeds (ingestion bindings) with their schedule — which datasets load, from where, how often. |
input · no output |
| 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. |
input · no output |
| list_inspection_sources List the row-level sources available for inspection. |
input · no output |
| list_kpis Browse the metric catalogue — metric keys, formats, domains, and the dimensions available per metric. |
input · no output |
| 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?". |
input · no output |
| list_scenarios List the available planning scenarios and their status. |
input · no output |
| list_variants List the what-if variants of a scenario. |
input · no output |
| 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. R |
input · no output |
| 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 × |
input · no output |
| 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 × |
input · no output |
| 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 optiona |
input · no output |
| 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 optiona |
input · no output |
| search_hierarchy Search the dimension hierarchies (cost centres, accounts, …) to find valid codes and ids before composing a query. |
input · no output |
Verify it yourself
npx teppi-check https://mcp.precis.finance/mcpcurl -s https://api.teppi.xyz/v1/trust/mcp/mcs_01M1FZ2MR74MC92YG72RY6KHTK