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šŸ‡ØšŸ‡¦ Bank of Canada Valet MCP Server

Python 3.10+ MCP License: MIT CI

An MCP server that gives LLM agents (Claude, and any other MCP-compatible client) live access to Canadian economic and financial data through the Bank of Canada Valet API — exchange rates, interest rates, inflation series, and thousands more.

The Valet API is free and requires no API key, so this server runs out of the box.

Ask "What's the latest USD/CAD exchange rate?" or "Chart CORRA over the last month" and the agent pulls the numbers straight from the source.


Why this exists

Large language models don't know today's exchange rate — their training data is frozen in the past. MCP closes that gap by letting a model call live tools. This server is a small, focused, production-shaped example of that pattern: clean tool design, input validation, actionable errors, and tests.

Related MCP server: mcp-statscan

Features

  • 5 well-scoped tools covering discovery → metadata → data retrieval

  • No API key — the Valet API is public

  • Dual output — human-readable Markdown or structured JSON, per call

  • Search + pagination over the large series/group catalogue

  • Multi-series comparison — pull several series side by side in one call

  • Agent-friendly errors — every failure explains what to try next

  • Typed & validated — Pydantic Field constraints on every parameter

  • Tested — offline unit tests, no network needed for CI

Tools

Tool

What it does

boc_list_series

Search / list the available data series (start here)

boc_list_groups

Search / list curated groups of related series

boc_get_series_info

Fetch metadata (label, description) for one series

boc_get_observations

Core: get data points for one or more series, by date range or most-recent

boc_get_group_observations

Get every series in a group in a single call

Architecture

src/boc_valet_mcp/
ā”œā”€ā”€ server.py       # MCP tool definitions (the interface agents see)
ā”œā”€ā”€ client.py       # Async httpx client + centralized, actionable errors
└── formatting.py   # Markdown / JSON rendering (shared by every tool)

The separation keeps each layer testable: tools stay thin, HTTP concerns live in one place, and presentation logic is unit-tested offline against representative payloads.

Quickstart

git clone https://github.com/Chatusvi-Karnati/boc-valet-mcp.git
cd boc-valet-mcp
python -m venv .venv && source .venv/bin/activate   # Windows: .venv\Scripts\activate
pip install -e .

Run it directly (it speaks MCP over stdio):

boc-valet-mcp

Inspect it interactively

The MCP Inspector is the fastest way to click through the tools:

npx @modelcontextprotocol/inspector boc-valet-mcp

Use it with Claude Desktop

Add this to your claude_desktop_config.json (see examples/):

{
  "mcpServers": {
    "bank-of-canada": {
      "command": "boc-valet-mcp"
    }
  }
}

Restart Claude Desktop and ask it something like "Compare the USD/CAD and EUR/CAD rates over the past week."

Example

Calling boc_get_observations with series_names="FXUSDCAD", recent=1:

**Series:**
- `FXUSDCAD` — US dollar to Canadian dollar daily exchange rate

| Date       | FXUSDCAD |
|------------|----------|
| 2024-06-03 | 1.3654   |

_1 observation(s)._

Development

pip install -e ".[dev]"
pytest              # run the test suite
ruff check .        # lint

How it was built

Designed and built following Anthropic's MCP server best practices — comprehensive tool coverage, readOnly/idempotent annotations, Pydantic-validated inputs, and error messages written for an agent audience. Developed with an AI-assisted workflow using Claude Code.

License

MIT — see LICENSE.

Acknowledgements

Data is provided by the Bank of Canada Valet API. This project is not affiliated with or endorsed by the Bank of Canada. Please review the Bank of Canada's terms of use for the data.

Available Tools

5 tools
boc_get_group_observationsA
Read-onlyIdempotent

Retrieve observations for every series in a group in one call.

For example group_name='FX_RATES_DAILY', recent=1 returns the latest daily exchange rate for all published currencies at once.

Inputs: group_name (required), recent, response_format. Returns: result

boc_get_observationsA
Read-onlyIdempotent

Retrieve observations (the actual data points) for one or more series.

This is the core tool. Supply a date range with 'start_date'/'end_date', or ask for the latest values with 'recent'. Multiple comma-separated series are returned side by side for easy comparison.

Example: series_names='FXUSDCAD', recent=1 returns the latest USD/CAD rate.

Inputs: series_names (required), recent, end_date, start_date, +1 more. Returns: result

boc_get_series_infoA
Read-onlyIdempotent

Get the label and description metadata for a single series.

Useful for confirming a series is what you expect before pulling its observations.

Inputs: name (required), response_format. Returns: result

boc_list_groupsA
Read-onlyIdempotent

Discover available data groups (curated bundles of related series).

Groups collect related series — for example 'FX_RATES_DAILY' bundles the daily exchange rates for many currencies. Feed a returned group name into 'boc_get_group_observations'.

Inputs: limit, offset, search, response_format. Returns: result

boc_list_seriesA
Read-onlyIdempotent

Discover available data series in the Bank of Canada Valet API.

Use this first when you do not already know a series name. Filter with 'search' to narrow the (large) catalogue, then feed a returned name into 'boc_get_observations'. Returns a paginated list of series with their name, label, and description.

Inputs: limit, offset, search, response_format. Returns: result

Tool Schema Changelog

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

Loading tool schema changelog…

    TDQS

    A4.2/5.0

    Scored across 5 tools

    Disambiguation5/5

    Each tool has a clear, distinct purpose: listing series, listing groups, getting series metadata, getting observations for series, and getting observations for groups. No overlap.

    Naming Consistency5/5

    All tools follow a consistent 'boc_verb_noun' pattern (e.g., boc_list_series, boc_get_observations), making it easy to infer functionality.

    Tool Count5/5

    With 5 tools, the server is focused and each tool earns its place. The count is ideal for a read-only economic data API.

    Completeness4/5

    Covers discovery and retrieval for both individual series and groups. Missing a dedicated tool for group metadata, but the list tool provides enough context.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

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