Categories › AI & Agents › Multi-agent, orchestration & workflows
Public read-only Précis Finance MCP demo with synthetic data; no account or credentials required.
Remote server: your requests and data go to mcp.precis.finance. Claude Code: claude mcp add --transport http pr-cis-finance-mcp https://mcp.precis.finance/mcp · Claude app: Settings → Connectors → Add custom connector.
The tools this server listed when we connected to it, in its own words.
precis_orientation — Call this first. Returns how to use Précis over this connector: the data model (scenarios, metrics, statements, dimensions), the reporting-tlist_scenarios — List the available planning scenarios and their status.list_kpis — Browse the metric catalogue — metric keys, formats, domains, and the dimensions available per metric.list_inspection_sources — List the row-level sources available for inspection.get_inspection_schema — Get the column schema for an inspection source.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 urun_statement — Run a financial statement — P&L, variance report, or executive summary. Rows are statement lines (Revenue, Direct Cost, Gross Margin, …); corun_statement_data — Run a financial statement — P&L, variance report, or executive summary. Rows are statement lines (Revenue, Direct Cost, Gross Margin, …); corun_metric — Break one or more metrics down by a dimension — revenue by project, utilisation by employee, headcount trends, GL account drill-down. Rows arun_metric_data — Break one or more metrics down by a dimension — revenue by project, utilisation by employee, headcount trends, GL account drill-down. Rows asearch_hierarchy — Search the dimension hierarchies (cost centres, accounts, …) to find valid codes and ids before composing a query.list_dimensions — List the dimensions defined in the model — keys, labels, and kinds (leaf / derived / ragged hierarchy). Catalogue metadata only; use search_list_variants — List the what-if variants of a scenario.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, waterfallexport_dataset — Export a previously returned data_ref to json or xlsx without rerunning the query. Use this for standard Excel exports of reports already shget_file_download — Renew a download capability for an available, owned artifact.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 get_load_status — Fetch one data load's full detail by load_id — timestamps, status, rows landed, and any error message.list_bindings — List the configured data feeds (ingestion bindings) with their schedule — which datasets load, from where, how often.get_binding — Fetch one data feed's full configuration: source, target dataset, schedule, and extract parameters.Not tested by KitScout yet. When our harness runs it, pros, cons and the tasks we tried appear here, with the date and evidence.