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MapleStats MCP

MapleStats MCP gives AI agents (Claude, Cursor and any MCP client) typed access to Canadian open data through one server: Statistics Canada (tables, Census, public use microdata), the Bank of Canada, CMHC, federal agencies, and federal, provincial, territorial and municipal open-data portals, in English and French. Every result carries its source.

MapleStats MCP donne aux agents IA un accès structuré aux données ouvertes canadiennes par un seul serveur, en français et en anglais.

Project vision: docs/PROJECT_GUIDE.md. Source coverage: docs/ROADMAP.md. Website: https://maplestats.danielstats.io/.

The easiest way: ask your agent

  1. Copy this prompt.

  2. Paste it into Claude Code, Codex, Cursor or any agent that can run commands on your computer.

  3. Restart the agent when it says so, then ask for data.

Connect the MapleStats MCP server to this agent. Follow the setup steps in https://github.com/dsanchezp18/maplestats-mcp

Instructions for the agent doing the setup

The default is the hosted server: nothing to install, no account, no key.

  1. Register this remote (HTTP) MCP server under the name maplestats:

    • Claude Code: claude mcp add --transport http --scope user maplestats https://maplestats-mcp.onrender.com/mcp

    • Codex CLI: codex mcp add maplestats --url https://maplestats-mcp.onrender.com/mcp

    • Cursor, Claude Desktop and other mcpServers clients: add the entry below to the client's config file (Cursor: ~/.cursor/mcp.json; Claude Desktop: ~/Library/Application Support/Claude/claude_desktop_config.json on macOS, %APPDATA%\Claude\claude_desktop_config.json on Windows), keeping any servers already there.

    • claude.ai and the Claude phone app: on the web, open Settings → Connectors → Add custom connector, name it MapleStats, and enter https://maplestats-mcp.onrender.com/mcp. Then switch it on from the tools menu in a chat, on the web or in the phone app. Claude asks for approval before each call by default; every tool is read-only, so set them to always allow in the connector's tool permissions.

    • ChatGPT (web): turn on Settings → Security and login → Developer mode, then create a developer-mode app for a remote MCP server with the same address and No Authentication. Every tool is read-only, so ChatGPT should not ask to confirm calls. OpenAI documents this feature for the web.

    • A whole organization: on Claude Team or Enterprise, an Owner adds it once under Organization settings → Connectors → Add custom connector, and each member then connects it. On ChatGPT Business, Enterprise or Edu, an admin turns on Developer mode (Workspace Settings → Permissions & Roles → Connected Data), creates the app, and publishes it (Workspace settings → Apps → Drafts → Publish). The hosted server is shared and limits each client to 60 requests a minute, so a large organization should run its own copy.

    • VS Code: the same entry under a servers key, with "type": "http", in .vscode/mcp.json.

    {
      "mcpServers": {
        "maplestats": {
          "url": "https://maplestats-mcp.onrender.com/mcp"
        }
      }
    }
  2. Tell the user to restart or reload the client, then check that the search_tools tool is listed.

  3. Only if the client cannot use remote servers, or the user wants the microdata tabulation tool or everything kept on their own machine, run it locally instead: claude mcp add --scope user maplestats -- uvx maplestats-mcp (needs uv), or the equivalent uvx maplestats-mcp entry for other clients (see Install).

The first request after a quiet spell can take up to a minute; if your client reports the server as failed, retry a minute later. Each client gets 60 requests a minute, and the microdata tabulation tool is switched off there. Your agent's tool calls (a search phrase, a table number) reach the server and its host, Render. The code keeps no log of them, but its in-memory cache can hold a search phrase or filter in a key or a response until the entry expires or the server restarts. Check Render's terms and privacy policy; for full privacy, run it locally. What it logs: FAQ. Other clients: the Connect page.

Related MCP server: Données Québec MCP

Install locally (optional)

Prefer to run it on your machine? It works over stdio with no account or key.

uvx maplestats-mcp                 # run without installing
uv tool install maplestats-mcp     # or install the command once (pip works too)
uv tool upgrade maplestats-mcp     # update

For the development version: uv tool install git+https://github.com/dsanchezp18/maplestats-mcp.git. If you installed the command, use "command": "maplestats-mcp" with no args in the JSON above. On Windows, make sure the directory where uv installs tools is on PATH, and restart the client afterwards.

Using it

Tools are found through search rather than listed flat: call search_tools with a plain-language query (English or French), then call_tool with the name it returns.

{"name": "search_tools", "arguments": {"query": "consumer price index"}}
{"name": "call_tool", "arguments": {"name": "wds_search_cubes", "arguments": {"query": "consumer price index"}}}

plan_query turns a question into an ordered, multi-source plan, and reproduce_code writes the R, Python, Stata or Julia script (or an Excel Power Query) that fetches the same data straight from the source; reproduce_workbook returns the rows as a formatted Excel workbook. Every tool accepts lang: "en"|"fr"; some sources only publish English content (for example Yukon's CKAN portal, the World Bank's indicator definitions and the PMPRB), so there lang changes the labels MapleStats adds, not the source's own text. Every response has a provenance block: source, URL, query time, freshness and limits. docs://catalogue describes every module in both languages. The guided prompts take lang too, and each docs://<module>/... resource has a French twin at docs://<module>/fr/... (for example docs://statcan/fr/pieges).

To call the sources from Python without MCP, see docs/library.md.

What to watch for

MapleStats retrieves data directly from the original sources and returns values as published. When a result is trimmed, scaled, cleaned or computed, it says so in its provenance block or its notes; series values come unscaled, with the scale factor beside them. When a source is down or blocks the request, the tool returns an error, not a silent gap or a substitute value.

The risk is in the use. An AI assistant can pick the wrong table, geography or reference period, and the answers, summaries and analysis it writes are AI-generated and can contain errors. For anything you would publish, spot-check a few figures against the source's own site and use reproduce_code to fetch them again outside the assistant. Publishers revise their figures, so a value retrieved today can differ from an earlier one.

Each dataset keeps its own licence and attribution terms, shown in the result's provenance; credit the publisher, not MapleStats. MapleStats is an independent project, not affiliated with or endorsed by Statistics Canada, the Bank of Canada, CMHC or any other data provider. It is provided as is, depends on upstream services that can change or go offline, and is not professional, legal or financial advice. Parts of the code and tests were written with AI assistance; the discovery benchmark's questions were written by one AI session and reviewed by a second, independent one, not yet by a person (tests/discovery_benchmark/REVIEW.md).

What it covers

380 tools in 75 modules. Run docs://catalogue for the full, bilingual list.

Area

Tool prefixes

Covers

Statistics Canada

wds_, sdmx_, sdmx_space_, rdaas_, cimt_, statcan_*

Tables and series, the extra SDMX spaces (energy information, shared data), classifications, Census Profiles 2001–2021, public use microdata (codebooks, weighted tables), merchandise trade by commodity (CIMT), open databases (LODE), The Daily, delta files, indicators, surveys, census geography

Bank of Canada

boc_

Valet series, groups, observations

CMHC

cmhc_, cmhc_dt_

Housing Market Information Portal and Excel data tables

Federal agencies

eccc_, eccc_coverages_, eccc_datamart_, ised_*, gazette_, tc_recalls_, recalls_, cdc_, cfia_, fcac_, finance_, cihi_, phac_infobase_, hc_*, pmra_, pmprb_, gc_infobase_, cer_, nrcan_*, dfo_iwls_, cgc_, nfd_, ircc_*, cbsa_, cbsa_tariff_, pbo_, competition_bureau_, elections_results_, elections_financial_returns_, cra_digital_economy_registry_, earthquakes_, borealis_, isc_

Weather, climate and gridded climate projections, pollutant releases and emissions (NPRI, GHGRP, NAPS), corporations and IP, regulations, recalls, dairy, animal disease, consumer banking, federal and provincial fiscal tables, health, drugs, natural health products, medical devices, adverse reactions, pesticides, spending, energy, mineral production, oceans, grain, forestry, immigration, border wait times, customs tariff rates, budgets, mergers, elections, earthquakes, university-library data tables, First Nation profiles, registered population and drinking water advisories

Wildland fire

cwfis_, nrcan_nbac_, ab_wildfire_

NRCan's Canadian Wildland Fire Information System (satellite hotspots, fire danger, weather stations), burned areas, and Alberta Wildfire's live fire status

Electricity

electricity_ontario_, electricity_quebec_, oeb_

IESO (Ontario) demand, generation and prices; Hydro-Québec demand, generation and trade (CC BY-NC 4.0: credit Hydro-Québec, non-commercial use only); Ontario Energy Board datasets

Parliament and elected officials

ourcommons_, senate_, represent_

MPs and their roles, party standings, Cabinet, Senate votes; elected officials and districts for a postal code via Open North's Represent (unofficial)

Provincial agencies

aer_, bcgw_, bc_stats_, bc_env_, bc_lobbyists_, drivebc_, ab_economic_, ab_opendata_, isq_, nl_stats_, yukon_stats_, nwt_stats_, elections_provincial_, on_fir_

Alberta Energy Regulator, BC Geographic Warehouse, BC Stats Excel tables, BC environmental monitoring (air quality, snow, groundwater, streamflow), BC lobbyists registry, DriveBC road events, Alberta Economic Dashboard, Open Alberta files, Institut de la statistique du Québec, the Newfoundland and Labrador, Yukon and Northwest Territories statistics bureaus, provincial general election results (Quebec, Alberta, British Columbia, Saskatchewan, Manitoba), Ontario's municipal Financial Information Return (every schedule of every municipality, 2000 on)

Housing (links only)

crea_

Links, release timing and terms for CREA's MLS® Home Price Index; no values, because CREA's terms allow private, non-commercial analysis only

International

worldbank_, bis_

World Bank World Development Indicators for Canada and peer countries (CC BY 4.0); Bank for International Settlements statistics: policy rates, debt service ratios, credit, house prices, banking and payment statistics (free reuse with citation)

Open-data portals

ckan_, arcgis_hub_, socrata_ + portal

Federal, provincial, territorial and municipal catalogues (*_list_portals names each one)

Other municipal

opendatasoft_vancouver_, nl_opendata_, eps_, ets_, epcor_

Vancouver, Newfoundland and Labrador, Edmonton police, transit and water quality

Transit schedules

transit_ + agency

Static GTFS timetables of the STM (buses), OC Transpo, Calgary Transit, VIA Rail, GO Transit, UP Express, the BC Transit systems and the Quebec networks listed on Données Québec (exo, RTC, STL, STS and others), plus further agencies from Statistics Canada's 2025 Canadian Public Transit Network Database: stops, routes, scheduled departures, frequency by hour

Other federal series (CRA, OSFI, ISED insolvency) are ordinary open.canada.ca datasets, reachable with ckan_search_datasets(portal="federal", fq="organization:<org>").

Not covered: CAPP's Statistics Handbook, Petrinex and Payments Canada were not built, because their terms or download hosts do not permit automated access. CanadaBuys, OpenParliament.ca and the Toronto Transit Commission's own schedule download were removed for the same reason (the TTC schedule is still served from Statistics Canada's national transit database), and the Saskatchewan GeoHub portal was removed. The 2006-2016 census data tables and the 2016 Census Profile service were removed because Statistics Canada's www12 host answers automated clients with a bot challenge, 503 errors or timeouts (the 2021 profile and the WDS tables remain). Justice Laws (federal statutes and regulations) is out of scope, because legislation text is not data this server carries, and the Saskatchewan Bureau of Statistics' Provincial Economic Accounts were not built: they are under Crown copyright, for non-commercial reuse only, and the site's terms bar automated access. The roadmap records each decision.

Development

uv sync                          # install
uv run ruff check src tests      # lint
uv run ruff format src tests     # format
uv run pyright                   # type check
uv run pytest                    # unit tests (mocked, no network)

.\scripts\verify.ps1 runs that gate plus every scripts/smoke_test*.py against the live APIs. The website is generated from the tool registry: uv run python scripts/build_site.py writes build/site/. See AGENTS.md for the contributor guide and how to add a source module.

Hosting

MAPLE_TRANSPORT=http MAPLE_HOST=0.0.0.0 MAPLE_PORT=8000 uv run maplestats-mcp serves HTTP instead of stdio; docker compose up --build does the same in Docker. Docker is optional and unnecessary on a personal computer. If the server is exposed beyond your machine, set MAPLE_AUTH_TOKEN and keep MAPLE_REQUIRE_AUTH=1. GET /health reports uptime and version. GET /stats is public, needs no token and reports calls per tool name and day, each tool's p50 and p95 duration, and each upstream host's error counts and circuit-breaker state (see MAPLE_USAGE_STATS and MAPLE_BREAKER below). After repeated failures (timeouts, connection errors, 5xx answers, Cloudflare challenges) a host is paused for a cooldown: its tools fail at once with an "unavailable" error that says when to retry, instead of waiting for another timeout. The docs://status resource lists the paused hosts.

Env var

Default

Purpose

MAPLE_TRANSPORT

stdio

stdio for local clients, http for hosting

MAPLE_HOST / MAPLE_PORT

127.0.0.1 / 8000

HTTP bind address

MAPLE_AUTH_TOKEN, MAPLE_REQUIRE_AUTH

unset, 0

Bearer token required on /mcp; refuse to start without one if 1. docker-compose.yml defaults MAPLE_REQUIRE_AUTH to 1

MAPLE_RATE_LIMIT_REQUESTS / MAPLE_RATE_LIMIT_WINDOW_SECONDS

120 / 60

Per-client rate limit

MAPLE_MAX_CONCURRENT_REQUESTS

8

In-flight request cap; the excess waits 5 s, then gets 503

MAPLE_SSL_CERTFILE / MAPLE_SSL_KEYFILE

unset

TLS in-process

MAPLE_TRUST_PROXY_HEADERS

0

Rate-limit on X-Forwarded-For; only behind a proxy that sets it

MAPLE_TRUSTED_PROXY_HOPS

1

Proxies that append to X-Forwarded-For; the client address is read that many entries from the right

MAPLE_ALLOWED_ORIGINS

project website, localhost

Browser origins allowed on /mcp (comma-separated, *. and :* wildcards); others get 403, clients without an Origin are allowed

MAPLE_CACHE_MAX_ENTRIES

2000

Response cache size per TTL bucket

MAPLE_CACHE_MAX_MB

128

Estimated memory cap for the response cache, all buckets together

MAPLE_PARSE_WORKERS / MAPLE_PARSE_TIMEOUT_SECONDS

4 / 60

Threads for parsing Excel and CSV files, and the time one parse may take

MAPLE_TOOL_TIMEOUT_SECONDS

120

Longest a tool call may run

MAPLE_BREAKER

1

Pause requests to an upstream host after repeated failures; 0 sends every request

MAPLE_BREAKER_FAILURES / MAPLE_BREAKER_WINDOW_SECONDS / MAPLE_BREAKER_COOLDOWN_SECONDS

5 / 300 / 60

Failures in a row, within the window, that pause a host, and how long before one probe request is sent

MAPLE_PUMF_TABULATE

1

0 hides statcan_pumf_tabulate (it downloads whole PUMF ZIPs); search, listings and codebooks stay

MAPLE_PUMF_CACHE_DIR, MAPLE_PUMF_CACHE_MAX_GB

system temp, 5

Downloaded microdata cache; use a persistent volume when hosted

MAPLE_CLIENT_IP_HEADER

unset

Header the outermost proxy sets to the caller's own address (Cloudflare's CF-Connecting-IP), used for the per-client rate limit when MAPLE_TRUST_PROXY_HEADERS is on; set it only when every request passes through that proxy

MAPLE_DUCKDB_MEMORY_LIMIT

unset

Memory limit for DuckDB queries over downloaded files (patents, open databases, microdata), such as 256MB; beyond it DuckDB spills to the temporary folder. Set it on a small hosted instance

MAPLE_LODE_CACHE_DIR, MAPLE_LODE_CACHE_MAX_GB

system temp, 3

Where StatCan open-database (LODE) archives are unpacked, and the size cap (least recently used files go first); use a persistent volume when hosted

MAPLE_LODE_MAX_DOWNLOAD_MB

300

Largest open-database archive one call may download; 0 turns downloads off

MAPLE_IP_HORIZONS_CACHE_DIR, MAPLE_IP_HORIZONS_CACHE_MAX_GB

system temp, 3

CIPO patent table cache

MAPLE_CBSA_TARIFF_CACHE_DIR

system temp

Customs Tariff editions as Parquet (under 1 MB each, newest 12 kept)

MAPLE_ON_FIR_CACHE_DIR, MAPLE_ON_FIR_CACHE_MAX_MB

system temp, 500

Ontario FIR years kept as Parquet (about 3 MB each); use a persistent volume when hosted

MAPLE_EXPORT_DIR

Downloads folder (home folder if there is none)

Where reproduce_workbook saves Excel workbooks on a local server

MAPLE_SEARCH, MAPLE_SEMANTIC_DIR

bm25, unset

hybrid fuses BM25 with a local multilingual-e5-small index (needs the [semantic] extra and python -m maplestats_mcp.shared.semantic build); off by default, see tests/discovery_benchmark/phase2.md

MAPLE_RESPONSE_MAX_BYTES

200000

Byte budget for one tool result (minimum 10,000); a larger result has its biggest lists trimmed, and provenance.limits says what was kept and how to get the rest

MAPLE_USAGE_STATS

1

Counts calls and durations per tool name and UTC day, and upstream errors per host (never arguments or client addresses), in memory, and serves them at the public /stats route; 0 turns both off

MAPLE_DELTA_MAX_SCAN_MB / MAPLE_DELTA_MAX_SCAN_SECONDS

400 / 75

How much of a Delta File one statcan_delta_read_table call streams (seconds kept 30 under the tool timeout)

MAPLE_DELTA_INDEX_DIR

system temp

Saved Delta File resume points (a few MB per day); off keeps them in memory only

License

MIT. Third-party notices are in THIRD_PARTY_NOTICES.md.

Security and conduct

Report a vulnerability privately through GitHub's private vulnerability reporting; see SECURITY.md. Changes are recorded in CHANGELOG.md, and community expectations in CODE_OF_CONDUCT.md.

Acknowledgments

MapleStats owes its architecture to EcuDataMCP, the MCP server for Ecuador's open data that I help maintain with DweskZ and its other contributors. Its approach to Canadian data owes much to the R developers who got there first: Jens von Bergmann (mountainMath) and his co-authors, including Dmitry Shkolnik (dshkol), Thierry Warin (statcanR), Valentin Lucet (rgovcan), and others. Thanks to them, and to everyone who publishes Canadian data in the open.

For other ways to get Canadian data, see the alternatives.

Available Tools

3 tools
call_toolCall a toolA
Destructive
Inspect

Run one data tool found through search_tools or plan_query.

Use for: executing a tool by exact name with arguments that match the inputSchema search_tools returned for it. Data tools read public sources (StatCan, Bank of Canada, open-data portals). reproduce_workbook can save an Excel file on a local stdio server; hosted exports return base64. Returns that tool's typed result, including a provenance block (source, URL, query time, freshness). Errors come back as MCP tool errors, not as data: an unknown or misspelled name raises 'Unknown tool' (search again for the exact name), invalid arguments raise a validation error naming the field, and upstream outages or empty matches raise a typed error explaining what to change. search_tools, call_tool and plan_query cannot be called through it; call them directly. Tool calls are subject to the server's timeout (MAPLE_TOOL_TIMEOUT_SECONDS, default 120).

NameRequiredDescriptionDefault
nameYesExact tool name as returned by search_tools or plan_query, e.g. 'boc_get_observations'.
argumentsNoObject matching that tool's inputSchema from search_tools. Omit or pass {} for a tool with no required parameters.

TDQS

A4.4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds valuable context beyond annotations: data tools read public sources, reproduce_workbook can save an Excel file locally or return base64 on hosted exports, results include a provenance block, errors are typed MCP tool errors, and calls are subject to MAPLE_TOOL_TIMEOUT_SECONDS. It does not explicitly characterize destructive or write behavior in general, but the annotations already flag destructiveHint=true and the description is consistent with that.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose and use case, then covers error behavior and timeout constraints. It is somewhat long, but most details are operationally useful for a meta-tool that dispatches other tools.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex dispatcher with no output schema, the description is complete enough: it explains the return shape including provenance, how errors are surfaced, which tools cannot be called through it, and the timeout environment variable.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents both parameters. The description reinforces that 'name' must be exact and that arguments must match the target tool's inputSchema, but adds little beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb+resource: 'Run one data tool found through search_tools or plan_query.' It clearly distinguishes call_tool from the discovery/planning siblings and explains the exact use case (executing a named tool with matching arguments).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly says when to use this tool ('executing a tool by exact name with arguments that match the inputSchema'), names where the name comes from (search_tools or plan_query), and states when not to use it ('search_tools, call_tool and plan_query cannot be called through it; call them directly').

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

plan_queryPlan queryA
Read-onlyIdempotent
Inspect

Plan which sources answer a question that may span several agencies.

Use for: the first call on a substantive question ("How have rents and interest rates moved in Calgary since 2020?"). Returns the topics it touches, the tools to call for each in order, local portals for any province or city named, and caveats on combining them. Then run the steps with call_tool. Read-only and offline: it matches the question against this server's source map and calls no external API. Use search_tools instead to find a single tool for a narrow, single-source need. lang='fr' gives the labels, purposes, caveats and guidance in French; tool and argument names stay as they are. Keywords: plan, which data source, where to find, combine sources, cross-source, question, research, Canada data. Mots-clés : planifier, quelle source de données, où trouver, combiner des sources, question, recherche, données canadiennes, statistiques.

NameRequiredDescriptionDefault
langNoen
questionYes

Output Schema

NameRequiredDescription
placesYes
topicsYesBest match first; at most 4.
guidanceYes
questionYes
provenanceYesWhere a result came from and how fresh/complete it is. Embedded in every module's response models (composition, not inheritance) so a tool can return `MyResult(provenance=..., ...)` without fighting Pydantic's model-inheritance rules for extra fields.
out_of_scopeNoSet when the question is about a place outside Canada that this server has no data for; topics and fallback steps are then empty.
fallback_stepsYesOnly when no topic matched.

TDQS

A4.6/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly, idempotent, closed-world and non-destructive, so the safety profile is covered; the description adds genuinely new behavior: it is offline, matches against this server's local source map, and calls no external API. It also previews the return surface (topics, ordered tools, local portals, caveats), which partly overlaps the output schema but usefully signals that it is a planning step, not a data fetch.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with purpose, then when-to-use, then return contents, then behavioral constraints, then bilingual keyword tail. Every section earns its place except the bilingual keyword list, which adds length that is only justified by search discoverability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a two-parameter planning tool with full annotations and an output schema, nothing an agent needs is missing: purpose, sequencing relative to both siblings, follow-up action, offline behavior, and language effects are all covered, so the description does not need to explain return values.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must carry semantics: it fully specifies the lang parameter's effect ('gives the labels, purposes, caveats and guidance in French; tool and argument names stay as they are'), which is non-obvious behavior. The question parameter is not described abstractly but is effectively conveyed through the sample question, leaving only explicit format/length guidance absent.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Plan which sources answer a question that may span several agencies') and immediately distinguishes itself from siblings by naming both call_tool (execution) and search_tools (single-source lookup). An agent can pick this tool without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly prescribes when to use it ('the first call on a substantive question'), gives a concrete trigger example, defines the follow-up flow ('Then run the steps with call_tool'), and names the exclusion case with the alternative ('Use search_tools instead ... narrow, single-source need'). Nothing is left to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

search_toolsSearch toolsA
Read-onlyIdempotent
Inspect

Find the right data tool for one specific need by plain-language search.

Use for: locating a tool when you know roughly what data you want (a StatCan table, Bank of Canada series, a city's open-data portal). Returns the best-matching tool definitions, ranked by relevance, each with its name, description and full input schema, in the same format as list_tools. Read-only; it searches this server's catalogue only and calls no external API. Use plan_query instead when a question may span several sources or you do not know where to start; use call_tool to run a tool once you have its name. Queries in English or French both work. An empty result means no tool matched: rephrase with topic words (e.g. 'housing starts' rather than 'CMHC table').

NameRequiredDescriptionDefault
queryYesWhat you need, in plain English or French, e.g. 'Calgary rent index' or 'taux de chômage Québec'. Topic words work better than tool names.

Output Schema

NameRequiredDescription
resultYes

TDQS

A4.9/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations cover the safety profile (readOnly/openWorld=false/idempotent), and the description adds genuinely new behavior: it searches only this server's catalogue, calls no external API, returns ranked best-matching tool definitions in list_tools format, and defines the empty-result case with recovery advice. These are traits the annotations cannot convey.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose is front-loaded in the first sentence, followed by use-for, boundaries, alternatives, and an edge-case recovery line. Every sentence carries distinct operational information with no filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter search tool with an output schema and full annotation coverage, nothing an agent needs is missing: trigger, scope, return shape, ranking behavior, language support, and failure recovery are all stated.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the single query parameter is already well documented, so the baseline is 3. The description adds meaningful strategy beyond the schema: queries work in English or French, and topic words beat tool names, which shapes how an agent should phrase the argument.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (find/search) and resource (data tool) plus the scoping constraint that it searches this server's catalogue only. It explicitly names what it is not (plan_query, call_tool), so an agent can distinguish it from siblings without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit 'Use for' trigger, then hands off with conditions: 'use plan_query instead when a question may span several sources or you do not know where to start' and 'use call_tool to run a tool once you have its name.' That is the full when/when-not/alternative set.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool updatev0.4.3
    • Changedplan_query2 fields changed
      • addedOutput schema / properties / provenance / properties / caveats
        Added value: +{
        +  "description": "Fitness-for-use cautions for this table or source, from MapleStats' rules (docs://planner/fitness-rules).",
        +  "items": {
        +    "type": "string"
        +  },
        +  "type": "array"
        +}
      • addedOutput schema / properties / provenance / properties / commercial_use
        Added value: +{
        +  "anyOf": [
        +    {
        +      "enum": [
        +        "allowed",
        +        "not_allowed",
        +        "varies",
        +        "unknown"
        +      ],
        +      "type": "string"
        +    },
        +    {
        +      "type": "null"
        +    }
        +  ],
        +  "default": null,
        +  "description": "Whether the licence allows commercial reuse without asking the publisher: 'allowed', 'not_allowed' (non-commercial use only, or written permission needed), 'varies' (each dataset or feed has its own licence: read licence) or 'unknown' (terms silent, conflicting or not found). Null when no licence applies. The conditions themselves are in licence."
        +}
  2. 1 tool updatev0.4.0
    • Changedplan_query1 field changed
      • changedOutput schema / properties / provenance / properties / reproduce / default
        Previous value: -"For R, Python, Stata and Julia scripts that fetch and clean this data, call reproduce_code with this tool's name and arguments."New value: +"For R, Python, Stata and Julia scripts that fetch and clean these data, call reproduce_code with this tool's name and arguments."
  3. 1 tool updatev0.2.0
    • Changedplan_query2 fields changed
      • addedOutput schema / properties / out_of_scope
        Added value: +{
        +  "anyOf": [
        +    {
        +      "type": "string"
        +    },
        +    {
        +      "type": "null"
        +    }
        +  ],
        +  "default": null,
        +  "description": "Set when the question is about a place outside Canada that this server has no data for; topics and fallback steps are then empty."
        +}
      • addedOutput schema / properties / provenance / properties / licence
        Added value: +{
        +  "anyOf": [
        +    {
        +      "type": "string"
        +    },
        +    {
        +      "type": "null"
        +    }
        +  ],
        +  "default": null,
        +  "description": "Licence and attribution the upstream publisher requires, when it has one (set for every Statistics Canada result)."
        +}
  4. 2 tool updatesv0.1.1
    • Changedcall_tool2 fields changed
      • changedInput schema / properties / arguments / description
        Previous value: -"Arguments to pass to the tool"New value: +"Object matching that tool's inputSchema from search_tools. Omit or pass {} for a tool with no required parameters."
      • changedInput schema / properties / name / description
        Previous value: -"The name of the tool to call"New value: +"Exact tool name as returned by search_tools or plan_query, e.g. 'boc_get_observations'."
    • Changedsearch_tools1 field changed
      • changedInput schema / properties / query / description
        Previous value: -"Natural language query to search for tools"New value: +"What you need, in plain English or French, e.g. 'Calgary rent index' or 'taux de chômage Québec'. Topic words work better than tool names."
  5. 3 tool updatesv0.1.0
    • First observedcall_tool
    • First observedplan_query
    • First observedsearch_tools

TDQS

A4.4/5.0

Scored across 3 tools

Disambiguation4/5

The three tools form a clean discovery/planning/execution triad, and each description explicitly states when to prefer the other (plan_query for multi-source questions, search_tools for a single narrow need, call_tool to execute). The only residual overlap is search_tools vs plan_query, both of which help an agent find the right tool, but the stated boundary (single source vs cross-source) resolves it in practice.

Naming Consistency4/5

All three follow a snake_case verb_noun pattern (plan_query, call_tool, search_tools), which is predictable and readable. Minor deviation in that the noun objects are inconsistent in scope and number (query vs tool vs tools), but the pattern is clear enough that an agent can infer new tool names.

Tool Count4/5

Three tools is on the lean side but justified here: the server is a gateway whose real surface (StatCan, BoC, open-data tools) is reached through search_tools and call_tool, so a thin meta-layer keeps the exposed surface small. A direct list_tools equivalent would round it out, but nothing feels padded or missing at this layer.

Completeness4/5

The surface covers the full workflow an agent needs: find a tool (search_tools), plan a multi-source investigation with ordering and caveats (plan_query), then execute with provenance and typed errors (call_tool). Gaps are minor — no batch/multi-tool execution, no direct catalogue listing or schema lookup without a search, and no result pagination — but each is workable via repeat calls.

Maintenance

ActivityActive
ResponsivenessUnresponsive

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