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Categories › Data & Databases › Vector databases & embeddings

MCP Analytics

MCP serverVerified domain · mcpanalytics.aiRemote● LiveAPI key needed

A statistical analyst in your AI chat: bring data and a question, get a citable, re-runnable report.

Install

Remote server: your requests and data go to api.mcpanalytics.ai. Claude Code: claude mcp add --transport http mcp-analytics https://api.mcpanalytics.ai/mcp/api-key · Claude app: Settings → Connectors → Add custom connector.

What it can do

The tools this server listed when we connected to it, in its own words.

  • account_link — Direct link to the right account page for anything not doable in chat: billing, browser upload, report management. Hand the user the link an
  • about — Platform documentation and info: how it works (Answer, Analytics, Custom Analytics), usage.
  • agent_advisor — AI help desk: which analysis fits your question, interpreting results, fixing errors. Multi-turn.
  • datasets_upload — Get your data in. Pass `data` as an array of row objects to create the dataset immediately and get a dataset_ref ready for path_resolver; om
  • datasets_list — List and search your uploaded datasets, with fuzzy matching on name, description, and tags. Returns each dataset's uuid:// reference (the `u
  • discover_tools — Browse the analyses you can run: the ones you commissioned plus the platform Standard Library (prebuilt tools; each result tagged source:'ow
  • tools_schema — Get an analysis's parameter schema. ALWAYS call before path_tool_run.
  • review_estimate — The estimate as you review it WITH the user: the question as understood, the estimated answer (sample, marked), every place and its question
  • adjust_estimate — Apply the user's layout wishes to the estimate's page through the layout agent; a new named arrangement, nothing overwritten, no number chan
  • find_precedent — Before estimating: how did we answer this objective before, on this data or any data? Prior packages and library runs with their tools, mapp
  • check_tool_fit — Before naming a library tool: does it fit THIS dataset for THIS question? Column mapping, missing required inputs, method-fit verdict, the p
  • package_status — Read an analytics package back: status, every run under it, the report link once delivered.
  • my_objects — List and search the objects you own across every question: the curated charts, tables and figures of each delivered package, grouped by obje
  • build_status — Check a commissioned build in-chat: stage progress, queue position, rejection reason if the data didn't match the objective, honest ETA, rep
  • ask_library — Ask a question across all your delivered analyses: a synthesized answer with citations back to specific reports.
  • reports_list — Your report library: every analysis delivered, with status and links. Pass semantic_query to search report content in plain language.
  • warehouse — Query your org's data warehouse free: browse the catalog (tables with column roles + computed metrics), semantically find data, plain-langua
  • schedules — Standing re-runs of analyses you own: action='create' (weekly/monthly against a re-runnable data reference, connector:// or an https:// link
  • reports_view — Get a shareable browser link for a report, viewable without authentication.
  • report_cards — Browse a delivered report's individual cards (charts, tables, insights) inline in chat.
  • path_resolver — Which path a question about data should take (reuse, rerun, answer, tool_run, estimate, bespoke, ask or none), with the reason, every path's
  • path_reuse — Hand back the report already delivered for this question on this data. Time: as path_resolver quotes.
  • path_rerun — Run a delivered analysis again, on its own dataset or a new one: the same tools and mappings, no rebuild. package_id may also be the person'
  • path_answer — A read of the data (a total, an average, a count, the top group), computed on every row, in this response. When the question is not a read i
  • path_tool_run — Run one or more tested library tools on this dataset, with charts and a written report. No custom build. Time: as path_resolver quotes.
  • path_estimate — A rough answer over a sample and the layout of the full report, for the person to confirm before anything is ordered. Time: as path_resolver
  • path_bespoke — Order a custom analysis built for this data from a confirmed estimate, optionally with library tools alongside. Needs the person's yes and a

KitScout test notes

Not tested by KitScout yet. When our harness runs it, pros, cons and the tasks we tried appear here, with the date and evidence.

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